Detection of Internal Short Circuit in Lithium Ion Battery Using Model-Based Switching Model Method

Directory of Open Access Journals (Sweden)

Minhwan Seo

2017-01-01

Full Text Available Early detection of an internal short circuit (ISCr in a Li-ion battery can prevent it from undergoing thermal runaway, and thereby ensure battery safety. In this paper, a model-based switching model method (SMM is proposed to detect the ISCr in the Li-ion battery. The SMM updates the model of the Li-ion battery with ISCr to improve the accuracy of ISCr resistance R I S C f estimates. The open circuit voltage (OCV and the state of charge (SOC are estimated by applying the equivalent circuit model, and by using the recursive least squares algorithm and the relation between OCV and SOC. As a fault index, the R I S C f is estimated from the estimated OCVs and SOCs to detect the ISCr, and used to update the model; this process yields accurate estimates of OCV and R I S C f . Then the next R I S C f is estimated and used to update the model iteratively. Simulation data from a MATLAB/Simulink model and experimental data verify that this algorithm shows high accuracy of R I S C f estimates to detect the ISCr, thereby helping the battery management system to fulfill early detection of the ISCr.

Model-based design and optimization of vanadium redox flow batteries

Energy Technology Data Exchange (ETDEWEB)

Koenig, Sebastian

2017-07-19

This work targets on increasing the efficiency of the Vanadium Redox Flow Battery (VRFB) using a model-based approach. First, a detailed instruction for setting up a VRFB model on a system level is given. Modelling of open-circuit-voltage, ohmic overpotential, concentration overpotential, Vanadium crossover, shunt currents as well as pump power demand is presented. All sub-models are illustrated using numerical examples. Using experimental data from three battery manufacturers, the voltage model validated. The identified deviations reveal deficiencies in the literature model. By correctly deriving the mass transfer coefficients and adapting the effective electrode area, these deficiencies are eliminated. The validated battery model is then deployed in an extensive design study. By varying the electrode area between 1000 and 4000 cm{sup 2} and varying the design of the electrolyte supply channel, twenty-four different cell designs are created using finite element analysis. These designs are subsequently simulated in 40-cell stacks deployed in systems with a single stack and systems with a three-stack string. Using the simulation results, the impact of different design parameters on different loss mechanisms is investigated. While operating the VRFB, the electrolyte flow rate is the most important operational parameter. A novel, model-based optimization strategy is presented and compared to established flow rate control strategies. Further, a voltage controller is introduced which delays the violation of cell voltage limits by controlling the flow rate as long as the pump capacity is not fully exploited.

Model-based design and optimization of vanadium redox flow batteries

International Nuclear Information System (INIS)

Koenig, Sebastian

2017-01-01

This work targets on increasing the efficiency of the Vanadium Redox Flow Battery (VRFB) using a model-based approach. First, a detailed instruction for setting up a VRFB model on a system level is given. Modelling of open-circuit-voltage, ohmic overpotential, concentration overpotential, Vanadium crossover, shunt currents as well as pump power demand is presented. All sub-models are illustrated using numerical examples. Using experimental data from three battery manufacturers, the voltage model validated. The identified deviations reveal deficiencies in the literature model. By correctly deriving the mass transfer coefficients and adapting the effective electrode area, these deficiencies are eliminated. The validated battery model is then deployed in an extensive design study. By varying the electrode area between 1000 and 4000 cm 2 and varying the design of the electrolyte supply channel, twenty-four different cell designs are created using finite element analysis. These designs are subsequently simulated in 40-cell stacks deployed in systems with a single stack and systems with a three-stack string. Using the simulation results, the impact of different design parameters on different loss mechanisms is investigated. While operating the VRFB, the electrolyte flow rate is the most important operational parameter. A novel, model-based optimization strategy is presented and compared to established flow rate control strategies. Further, a voltage controller is introduced which delays the violation of cell voltage limits by controlling the flow rate as long as the pump capacity is not fully exploited.

Modelling of rechargeable NiMH batteries

NARCIS (Netherlands)

Ledovskikh, A.; Verbitskiy, E.; Ayeb, A.; Notten, P.H.L.

2003-01-01

A new mathematical model has been developed for rechargeable NiMH batteries, which is based on the occurring physical–chemical processes inside. This model enables one to simultaneously simulate the battery voltage, internal gas pressures (both PO2 and PH2) and temperature during battery operation.

Adaptive State of Charge Estimation for Li-Ion Batteries Based on an Unscented Kalman Filter with an Enhanced Battery Model

Directory of Open Access Journals (Sweden)

Yuanyuan Liu

2013-08-01

Full Text Available Accurate estimation of the state of charge (SOC of batteries is one of the key problems in a battery management system. This paper proposes an adaptive SOC estimation method based on unscented Kalman filter algorithms for lithium (Li-ion batteries. First, an enhanced battery model is proposed to include the impacts due to different discharge rates and temperatures. An adaptive joint estimation of the battery SOC and battery internal resistance is then presented to enhance system robustness with battery aging. The SOC estimation algorithm has been developed and verified through experiments on different types of Li-ion batteries. The results indicate that the proposed method provides an accurate SOC estimation and is computationally efficient, making it suitable for embedded system implementation.

Model-based dynamic multi-parameter method for peak power estimation of lithium-ion batteries

NARCIS (Netherlands)

Sun, F.; Xiong, R.; He, H.; Li, W.; Aussems, J.E.E.

2012-01-01

A model-based dynamic multi-parameter method for peak power estimation is proposed for batteries and battery management systems (BMSs) used in hybrid electric vehicles (HEVs). The available power must be accurately calculated in order to not damage the battery by over charging or over discharging or

Battery Modeling: A Versatile Tool to Design Advanced Battery Management Systems

NARCIS (Netherlands)

Notten, P.H.L.; Danilov, D.L.

Fundamental physical and (electro) chemical principles of rechargeable battery operation form the basis of the electronic network models developed for Nickel-based aqueous battery systems, including Nickel Metal Hydride (NiMH), and non-aqueous battery systems, such as the well-known Li-ion. Refined

On-board adaptive model for state of charge estimation of lithium-ion batteries based on Kalman filter with proportional integral-based error adjustment

Science.gov (United States)

Wei, Jingwen; Dong, Guangzhong; Chen, Zonghai

2017-10-01

With the rapid development of battery-powered electric vehicles, the lithium-ion battery plays a critical role in the reliability of vehicle system. In order to provide timely management and protection for battery systems, it is necessary to develop a reliable battery model and accurate battery parameters estimation to describe battery dynamic behaviors. Therefore, this paper focuses on an on-board adaptive model for state-of-charge (SOC) estimation of lithium-ion batteries. Firstly, a first-order equivalent circuit battery model is employed to describe battery dynamic characteristics. Then, the recursive least square algorithm and the off-line identification method are used to provide good initial values of model parameters to ensure filter stability and reduce the convergence time. Thirdly, an extended-Kalman-filter (EKF) is applied to on-line estimate battery SOC and model parameters. Considering that the EKF is essentially a first-order Taylor approximation of battery model, which contains inevitable model errors, thus, a proportional integral-based error adjustment technique is employed to improve the performance of EKF method and correct model parameters. Finally, the experimental results on lithium-ion batteries indicate that the proposed EKF with proportional integral-based error adjustment method can provide robust and accurate battery model and on-line parameter estimation.

State of Charge Estimation Using the Extended Kalman Filter for Battery Management Systems Based on the ARX Battery Model

Directory of Open Access Journals (Sweden)

Hongjie Wu

2013-01-01

Full Text Available State of charge (SOC is a critical factor to guarantee that a battery system is operating in a safe and reliable manner. Many uncertainties and noises, such as fluctuating current, sensor measurement accuracy and bias, temperature effects, calibration errors or even sensor failure, etc. pose a challenge to the accurate estimation of SOC in real applications. This paper adds two contributions to the existing literature. First, the auto regressive exogenous (ARX model is proposed here to simulate the battery nonlinear dynamics. Due to its discrete form and ease of implemention, this straightforward approach could be more suitable for real applications. Second, its order selection principle and parameter identification method is illustrated in detail in this paper. The hybrid pulse power characterization (HPPC cycles are implemented on the 60AH LiFePO4 battery module for the model identification and validation. Based on the proposed ARX model, SOC estimation is pursued using the extended Kalman filter. Evaluation of the adaptability of the battery models and robustness of the SOC estimation algorithm are also verified. The results indicate that the SOC estimation method using the Kalman filter based on the ARX model shows great performance. It increases the model output voltage accuracy, thereby having the potential to be used in real applications, such as EVs and HEVs.

Influence of Battery Parametric Uncertainties on the State-of-Charge Estimation of Lithium Titanate Oxide-Based Batteries

DEFF Research Database (Denmark)

Stroe, Ana-Irina; Meng, Jinhao; Stroe, Daniel-Ioan

2018-01-01

to describe the battery dynamics. The SOC estimation method proposed in this paper is based on an Extended Kalman Filter (EKF) and nonlinear battery model which was parameterized using extended laboratory tests performed on several 13 Ah lithium titanate oxide (LTO)-based lithium-ion batteries. The developed......State of charge (SOC) is one of the most important parameters in battery management systems, as it indicates the available battery capacity at every moment. There are numerous battery model-based methods used for SOC estimation, the accuracy of which depends on the accuracy of the model considered...... a sensitivity analysis it was showed that the SOC and voltage estimation error are only slightly dependent on the variation of the battery model parameters with the SOC....

Modeling for Battery Prognostics

Science.gov (United States)

Kulkarni, Chetan S.; Goebel, Kai; Khasin, Michael; Hogge, Edward; Quach, Patrick

2017-01-01

For any battery-powered vehicles (be it unmanned aerial vehicles, small passenger aircraft, or assets in exoplanetary operations) to operate at maximum efficiency and reliability, it is critical to monitor battery health as well performance and to predict end of discharge (EOD) and end of useful life (EOL). To fulfil these needs, it is important to capture the battery's inherent characteristics as well as operational knowledge in the form of models that can be used by monitoring, diagnostic, and prognostic algorithms. Several battery modeling methodologies have been developed in last few years as the understanding of underlying electrochemical mechanics has been advancing. The models can generally be classified as empirical models, electrochemical engineering models, multi-physics models, and molecular/atomist. Empirical models are based on fitting certain functions to past experimental data, without making use of any physicochemical principles. Electrical circuit equivalent models are an example of such empirical models. Electrochemical engineering models are typically continuum models that include electrochemical kinetics and transport phenomena. Each model has its advantages and disadvantages. The former type of model has the advantage of being computationally efficient, but has limited accuracy and robustness, due to the approximations used in developed model, and as a result of such approximations, cannot represent aging well. The latter type of model has the advantage of being very accurate, but is often computationally inefficient, having to solve complex sets of partial differential equations, and thus not suited well for online prognostic applications. In addition both multi-physics and atomist models are computationally expensive hence are even less suited to online application An electrochemistry-based model of Li-ion batteries has been developed, that captures crucial electrochemical processes, captures effects of aging, is computationally efficient

An averaging battery model for a lead-acid battery operating in an electric car

Science.gov (United States)

Bozek, J. M.

1979-01-01

A battery model is developed based on time averaging the current or power, and is shown to be an effective means of predicting the performance of a lead acid battery. The effectiveness of this battery model was tested on battery discharge profiles expected during the operation of an electric vehicle following the various SAE J227a driving schedules. The averaging model predicts the performance of a battery that is periodically charged (regenerated) if the regeneration energy is assumed to be converted to retrievable electrochemical energy on a one-to-one basis.

A computationally efficient implementation of a full and reduced-order electrochemistry-based model for Li-Ion batteries

NARCIS (Netherlands)

Xia, L.; Najafi, E.; Li, Z.; Bergveld, H.J.; Donkers, M.C.F.

2017-01-01

Lithium-ion batteries are commonly employed in various applications owing to high energy density and long service life. Lithium-ion battery models are used for analysing batteries and enabling power control in applications. The Doyle-Fuller-Newman (DFN) model is a popular electrochemistry-based

Three Dimensional Thermal Modeling of Li-Ion Battery Pack Based on Multiphysics and Calorimetric Measurement

DEFF Research Database (Denmark)

Khan, Mohammad Rezwan; Kær, Søren Knudsen

2016-01-01

A three-dimensional multiphysics-based thermal model of a battery pack is presented. The model is intended to demonstrate the cooling mechanism inside the battery pack. Heat transfer (HT) and computational fluid dynamics (CFD) physics are coupled for both time-dependent and steady-state simulatio...

Electrical circuit models for performance modeling of Lithium-Sulfur batteries

DEFF Research Database (Denmark)

Knap, Vaclav; Stroe, Daniel Ioan; Teodorescu, Remus

2015-01-01

emerging technology for various applications, there is a need for Li-S battery performance model; however, developing such models represents a challenging task due to batteries' complex ongoing chemical reactions. Therefore, the literature review was performed to summarize electrical circuit models (ECMs......) used for modeling the performance behavior of Li-S batteries. The studied Li-S pouch cell was tested in the laboratory in order to parametrize four basic ECM topologies. These topologies were compared by analyzing their voltage estimation accuracy values, which were obtained for different battery...... current profiles. Based on these results, the 3 R-C ECM was chosen and the Li-S battery cell discharging performance model with current dependent parameters was derived and validated....

An Empirical Rate Constant Based Model to Study Capacity Fading in Lithium Ion Batteries

Directory of Open Access Journals (Sweden)

Srivatsan Ramesh

2015-01-01

Full Text Available A one-dimensional model based on solvent diffusion and kinetics to study the formation of the SEI (solid electrolyte interphase layer and its impact on the capacity of a lithium ion battery is developed. The model uses the earlier work on silicon oxidation but studies the kinetic limitations of the SEI growth process. The rate constant of the SEI formation reaction at the anode is seen to play a major role in film formation. The kinetics of the reactions for capacity fading for various battery systems are studied and the rate constants are evaluated. The model is used to fit the capacity fade in different battery systems.

An advanced Lithium-ion battery optimal charging strategy based on a coupled thermoelectric model

International Nuclear Information System (INIS)

Liu, Kailong; Li, Kang; Yang, Zhile; Zhang, Cheng; Deng, Jing

2017-01-01

Lithium-ion batteries are widely adopted as the power supplies for electric vehicles. A key but challenging issue is to achieve optimal battery charging, while taking into account of various constraints for safe, efficient and reliable operation. In this paper, a triple-objective function is first formulated for battery charging based on a coupled thermoelectric model. An advanced optimal charging strategy is then proposed to develop the optimal constant-current-constant-voltage (CCCV) charge current profile, which gives the best trade-off among three conflicting but important objectives for battery management. To be specific, a coupled thermoelectric battery model is first presented. Then, a specific triple-objective function consisting of three objectives, namely charging time, energy loss, and temperature rise (both the interior and surface), is proposed. Heuristic methods such as Teaching-learning-based-optimization (TLBO) and particle swarm optimization (PSO) are applied to optimize the triple-objective function, and their optimization performances are compared. The impacts of the weights for different terms in the objective function are then assessed. Experimental results show that the proposed optimal charging strategy is capable of offering desirable effective optimal charging current profiles and a proper trade-off among the conflicting objectives. Further, the proposed optimal charging strategy can be easily extended to other battery types.

A self-discharge model of Lithium-Sulfur batteries based on direct shuttle current measurement

DEFF Research Database (Denmark)

Knap, Vaclav; Stroe, Daniel Loan; Swierczynski, Maciej Jozef

2016-01-01

. A simple but comprehensive mathematical model of the Li-S battery cell self-discharge based on the shuttle current was developed and is presented. The shuttle current values for the model parameterization were obtained from the direct shuttle current measurements. Furthermore, the battery cell depth......-of-discharge values were recomputed in order to account for the influence of the self-discharge and provide a higher accuracy of the model. Finally, the derived model was successfully validated against laboratory experiments at various conditions....

Performance-degradation model for Li4Ti5O12-based battery cells used in wind power applications

DEFF Research Database (Denmark)

Stroe, Daniel Ioan; Swierczynski, Maciej Jozef; Stan, Ana-Irina

2012-01-01

Energy storage systems based on Lithium-ion batteries have the potential to mitigate the negative impact of wind power grid integration on the power system stability, which is caused by the characteristics of the wind. This paper presents a performance model for a Li4Ti5O12/LiMO2 battery cell....... For developing the performance model an EIS-based electrical modelling approach was followed. The obtained model is able to predict with high accuracy charge and discharge voltage profiles for different ages of the battery cell and for different charging/discharging current rates. Moreover, the ageing behaviour...... of the battery cell was analysed for the case of accelerated cycling ageing with a certain mission profile....

End-of-Discharge and End-of-Life Prediction in Lithium-Ion Batteries with Electrochemistry-Based Aging Models

Science.gov (United States)

Daigle, Matthew; Kulkarni, Chetan S.

2016-01-01

As batteries become increasingly prevalent in complex systems such as aircraft and electric cars, monitoring and predicting battery state of charge and state of health becomes critical. In order to accurately predict the remaining battery power to support system operations for informed operational decision-making, age-dependent changes in dynamics must be accounted for. Using an electrochemistry-based model, we investigate how key parameters of the battery change as aging occurs, and develop models to describe aging through these key parameters. Using these models, we demonstrate how we can (i) accurately predict end-of-discharge for aged batteries, and (ii) predict the end-of-life of a battery as a function of anticipated usage. The approach is validated through an experimental set of randomized discharge profiles.

A multi-timescale estimator for battery state of charge and capacity dual estimation based on an online identified model

International Nuclear Information System (INIS)

Wei, Zhongbao; Zhao, Jiyun; Ji, Dongxu; Tseng, King Jet

2017-01-01

Highlights: •SOC and capacity are dually estimated with online adapted battery model. •Model identification and state dual estimate are fully decoupled. •Multiple timescales are used to improve estimation accuracy and stability. •The proposed method is verified with lab-scale experiments. •The proposed method is applicable to different battery chemistries. -- Abstract: Reliable online estimation of state of charge (SOC) and capacity is critically important for the battery management system (BMS). This paper presents a multi-timescale method for dual estimation of SOC and capacity with an online identified battery model. The model parameter estimator and the dual estimator are fully decoupled and executed with different timescales to improve the model accuracy and stability. Specifically, the model parameters are online adapted with the vector-type recursive least squares (VRLS) to address the different variation rates of them. Based on the online adapted battery model, the Kalman filter (KF)-based SOC estimator and RLS-based capacity estimator are formulated and integrated in the form of dual estimation. Experimental results suggest that the proposed method estimates the model parameters, SOC, and capacity in real time with fast convergence and high accuracy. Experiments on both lithium-ion battery and vanadium redox flow battery (VRB) verify the generality of the proposed method on multiple battery chemistries. The proposed method is also compared with other existing methods on the computational cost to reveal its superiority for practical application.

Dynamic Prediction of Power Storage and Delivery by Data-Based Fractional Differential Models of a Lithium Iron Phosphate Battery

Directory of Open Access Journals (Sweden)

Yunfeng Jiang

2016-07-01

Full Text Available A fractional derivative system identification approach for modeling battery dynamics is presented in this paper, where fractional derivatives are applied to approximate non-linear dynamic behavior of a battery system. The least squares-based state-variable filter (LSSVF method commonly used in the identification of continuous-time models is extended to allow the estimation of fractional derivative coefficents and parameters of the battery models by monitoring a charge/discharge demand signal and a power storage/delivery signal. In particular, the model is combined by individual fractional differential models (FDMs, where the parameters can be estimated by a least-squares algorithm. Based on experimental data, it is illustrated how the fractional derivative model can be utilized to predict the dynamics of the energy storage and delivery of a lithium iron phosphate battery (LiFePO 4 in real-time. The results indicate that a FDM can accurately capture the dynamics of the energy storage and delivery of the battery over a large operating range of the battery. It is also shown that the fractional derivative model exhibits improvements on prediction performance compared to standard integer derivative model, which in beneficial for a battery management system.

Passive hybridization of a photovoltaic module with lithium-ion battery cells: A model-based analysis

Science.gov (United States)

Joos, Stella; Weißhar, Björn; Bessler, Wolfgang G.

2017-04-01

Standard photovoltaic battery systems based on AC or DC architectures require power electronics and controllers, including inverters, MPP tracker, and battery charger. Here we investigate an alternative system design based on the parallel connection of a photovoltaic module with battery cells without any intermediate voltage conversion. This approach, for which we use the term passive hybridization, is based on matching the solar cell's and battery cell's respective current/voltage behavior. A battery with flat discharge characteristics can allow to pin the solar cell to its maximum power point (MPP) independently of the external power consumption. At the same time, upon battery full charge, voltage increase will drive the solar cell towards zero current and therefore self-prevent battery overcharge. We present a modeling and simulation analysis of passively hybridizing a 5 kWp PV system with a 5 kWh LFP/graphite lithium-ion battery. Dynamic simulations with 1-min time resolution are carried out for three exemplary summer and winter days using historic weather data and a synthetic single-family household consumer profile. The results demonstrate the feasibility of the system. The passive hybrid allows for high self-sufficiencies of 84.6% in summer and 25.3% in winter, which are only slightly lower than those of a standard system.

Development of a lifetime prediction model for lithium-ion batteries based on extended accelerated aging test data

Science.gov (United States)

Ecker, Madeleine; Gerschler, Jochen B.; Vogel, Jan; Käbitz, Stefan; Hust, Friedrich; Dechent, Philipp; Sauer, Dirk Uwe

2012-10-01

Battery lifetime prognosis is a key requirement for successful market introduction of electric and hybrid vehicles. This work aims at the development of a lifetime prediction approach based on an aging model for lithium-ion batteries. A multivariable analysis of a detailed series of accelerated lifetime experiments representing typical operating conditions in hybrid electric vehicle is presented. The impact of temperature and state of charge on impedance rise and capacity loss is quantified. The investigations are based on a high-power NMC/graphite lithium-ion battery with good cycle lifetime. The resulting mathematical functions are physically motivated by the occurring aging effects and are used for the parameterization of a semi-empirical aging model. An impedance-based electric-thermal model is coupled to the aging model to simulate the dynamic interaction between aging of the battery and the thermal as well as electric behavior. Based on these models different drive cycles and management strategies can be analyzed with regard to their impact on lifetime. It is an important tool for vehicle designers and for the implementation of business models. A key contribution of the paper is the parameterization of the aging model by experimental data, while aging simulation in the literature usually lacks a robust empirical foundation.

Exploring the Model Design Space for Battery Health Management

Science.gov (United States)

Saha, Bhaskar; Quach, Cuong Chi; Goebel, Kai Frank

2011-01-01

Battery Health Management (BHM) is a core enabling technology for the success and widespread adoption of the emerging electric vehicles of today. Although battery chemistries have been studied in detail in literature, an accurate run-time battery life prediction algorithm has eluded us. Current reliability-based techniques are insufficient to manage the use of such batteries when they are an active power source with frequently varying loads in uncertain environments. The amount of usable charge of a battery for a given discharge profile is not only dependent on the starting state-of-charge (SOC), but also other factors like battery health and the discharge or load profile imposed. This paper presents a Particle Filter (PF) based BHM framework with plug-and-play modules for battery models and uncertainty management. The batteries are modeled at three different levels of granularity with associated uncertainty distributions, encoding the basic electrochemical processes of a Lithium-polymer battery. The effects of different choices in the model design space are explored in the context of prediction performance in an electric unmanned aerial vehicle (UAV) application with emulated flight profiles.

Lithium iron phosphate based battery – Assessment of the aging parameters and development of cycle life model

International Nuclear Information System (INIS)

Omar, Noshin; Monem, Mohamed Abdel; Firouz, Yousef; Salminen, Justin; Smekens, Jelle; Hegazy, Omar; Gaulous, Hamid; Mulder, Grietus; Van den Bossche, Peter; Coosemans, Thierry; Van Mierlo, Joeri

2014-01-01

Highlights: • Extended life cycle tests. • Investigation of the battery life cycle at different working conditions. • Investigation of the impact fast charging on the battery performances. • Extraction all required relationship for development of a cycle life model. • Development of a new life cycle model. - Abstract: This paper represents the evaluation of ageing parameters in lithium iron phosphate based batteries, through investigating different current rates, working temperatures and depths of discharge. From these analyses, one can derive the impact of the working temperature on the battery performances over its lifetime. At elevated temperature (40 °C), the performances are less compared to at 25 °C. The obtained mathematical expression of the cycle life as function of the operating temperature reveals that the well-known Arrhenius law cannot be applied to derive the battery lifetime from one temperature to another. Moreover, a number of cycle life tests have been performed to illustrate the long-term capabilities of the proposed battery cells at different discharge constant current rates. The results reveal the harmful impact of high current rates on battery characteristics. On the other hand, the cycle life test at different depth of discharge levels indicates that the battery is able to perform 3221 cycles (till 80% DoD) compared to 34,957 shallow cycles (till 20% DoD). To investigate the cycle life capabilities of lithium iron phosphate based battery cells during fast charging, cycle life tests have been carried out at different constant charge current rates. The experimental analysis indicates that the cycle life of the battery degrades the more the charge current rate increases. From this analysis, one can conclude that the studied lithium iron based battery cells are not recommended to be charged at high current rates. This phenomenon affects the viability of ultra-fast charging systems. Finally, a cycle life model has been developed, which

Battery sizing and rule-based operation of grid-connected photovoltaic-battery system: A case study in Sweden

International Nuclear Information System (INIS)

Zhang, Yang; Lundblad, Anders; Campana, Pietro Elia; Benavente, F.; Yan, Jinyue

2017-01-01

Highlights: • Battery sizing and rule-based operation are achieved concurrently. • Hybrid operation strategy that combines different strategies is proposed. • Three operation strategies are compared through multi-objective optimization. • High Net Present Value and Self Sufficiency Ratio are achieved at the same time. - Abstract: The optimal components design for grid-connected photovoltaic-battery systems should be determined with consideration of system operation. This study proposes a method to simultaneously optimize the battery capacity and rule-based operation strategy. The investigated photovoltaic-battery system is modeled using single diode photovoltaic model and Improved Shepherd battery model. Three rule-based operation strategies—including the conventional operation strategy, the dynamic price load shifting strategy, and the hybrid operation strategy—are designed and evaluated. The rule-based operation strategies introduce different operation parameters to run the system operation. multi-objective Genetic Algorithm is employed to optimize the decisional variables, including battery capacity and operation parameters, towards maximizing the system’s Self Sufficiency Ratio and Net Present Value. The results indicate that employing battery with the conventional operation strategy is not profitable, although it increases Self Sufficiency Ratio. The dynamic price load shifting strategy has similar performance with the conventional operation strategy because the electricity price variation is not large enough. The proposed hybrid operation strategy outperforms other investigated strategies. When the battery capacity is lower than 72 kW h, Self Sufficiency Ratio and Net Present Value increase simultaneously with the battery capacity.

Modeling, design, fabrication and experimentation of a GaN-based, 63Ni betavoltaic battery

Science.gov (United States)

E Munson, C., IV; Gaimard, Q.; Merghem, K.; Sundaram, S.; Rogers, D. J.; de Sanoit, J.; Voss, P. L.; Ramdane, A.; Salvestrini, J. P.; Ougazzaden, A.

2018-01-01

GaN is a durable, radiation hard and wide-bandgap semiconductor material, making it ideal for usage with betavoltaic batteries. This paper describes the design, fabrication and experimental testing of 1 cm2 GaN-based betavoltaic batteries (that achieve an output power of 2.23 nW) along with a full model that accurately simulates the device performance which is the highest to date (to the best of our knowledge) for GaN-based devices with a 63Ni source.

Modeling of electric vehicle battery for vehicle-to-grid applications

DEFF Research Database (Denmark)

Pang, Ying; Brady, Cormac; Pellegrino, Giustino

2013-01-01

Electric vehicle battery models are essential when performing analysis of EV systems. The battery package of electric vehicles is complicated and unpredictable because of its chemical based functioning. In this paper, a battery model is presented with a number of internal and external factors taken...

A model-based adaptive state of charge estimator for a lithium-ion battery using an improved adaptive particle filter

International Nuclear Information System (INIS)

Ye, Min; Guo, Hui; Cao, Binggang

2017-01-01

Highlights: • Propose an improved adaptive particle swarm filter method. • The SoC estimation method for the battery based on the adaptive particle swarm filter is presented. • The algorithm is validated by the case study of different aged extent batteries. • The effectiveness and applicability of the algorithm are validated by the LiPB batteries. - Abstract: Obtaining accurate parameters, state of charge (SoC) and capacity of a lithium-ion battery is crucial for a battery management system, and establishing a battery model online is complex. In addition, the errors and perturbations of the battery model dramatically increase throughout the battery lifetime, making it more challenging to model the battery online. To overcome these difficulties, this paper provides three contributions: (1) To improve the robustness of the adaptive particle filter algorithm, an error analysis method is added to the traditional adaptive particle swarm algorithm. (2) An online adaptive SoC estimator based on the improved adaptive particle filter is presented; this estimator can eliminate the estimation error due to battery degradation and initial SoC errors. (3) The effectiveness of the proposed method is verified using various initial states of lithium nickel manganese cobalt oxide (NMC) cells and lithium-ion polymer (LiPB) batteries. The experimental analysis shows that the maximum errors are less than 1% for both the voltage and SoC estimations and that the convergence time of the SoC estimation decreased to 120 s.

Model of Ni-63 battery with realistic PIN structure

Science.gov (United States)

Munson, Charles E.; Arif, Muhammad; Streque, Jeremy; Belahsene, Sofiane; Martinez, Anthony; Ramdane, Abderrahim; El Gmili, Youssef; Salvestrini, Jean-Paul; Voss, Paul L.; Ougazzaden, Abdallah

2015-09-01

GaN, with its wide bandgap of 3.4 eV, has emerged as an efficient material for designing high-efficiency betavoltaic batteries. An important part of designing efficient betavoltaic batteries involves a good understanding of the full process, from the behavior of the nuclear material and the creation of electron-hole pairs all the way through the collection of photo-generated carriers. This paper presents a detailed model based on Monte Carlo and Silvaco for a GaN-based betavoltaic battery device, modeled after Ni-63 as an energy source. The accuracy of the model is verified by comparing it with experimental values obtained for a GaN-based p-i-n structure under scanning electron microscope illumination.

Model of Ni-63 battery with realistic PIN structure

Energy Technology Data Exchange (ETDEWEB)

Munson, Charles E.; Voss, Paul L.; Ougazzaden, Abdallah, E-mail: aougazza@georgiatech-metz.fr [Georgia Tech Lorraine, Georgia Tech-C.N.R.S., UMI2958, 2-3 rue Marconi, 57070 Metz (France); School of Electrical and Computer Engineering, Georgia Institute of Technology, 777 Atlantic Drive NW, 30332-0250 Atlanta (United States); Arif, Muhammad; Salvestrini, Jean-Paul [Georgia Tech Lorraine, Georgia Tech-C.N.R.S., UMI2958, 2-3 rue Marconi, 57070 Metz (France); Université de Lorraine, CentraleSupélec, LMOPS, EA 4423, 2 rue E. Belin, 57070 Metz (France); Streque, Jeremy; El Gmili, Youssef [Georgia Tech Lorraine, Georgia Tech-C.N.R.S., UMI2958, 2-3 rue Marconi, 57070 Metz (France); Belahsene, Sofiane; Martinez, Anthony; Ramdane, Abderrahim [Laboratory for Photonics and Nanostructures, CNRS, Route de Nozay, 91460 Marcoussis (France)

2015-09-14

GaN, with its wide bandgap of 3.4 eV, has emerged as an efficient material for designing high-efficiency betavoltaic batteries. An important part of designing efficient betavoltaic batteries involves a good understanding of the full process, from the behavior of the nuclear material and the creation of electron-hole pairs all the way through the collection of photo-generated carriers. This paper presents a detailed model based on Monte Carlo and Silvaco for a GaN-based betavoltaic battery device, modeled after Ni-63 as an energy source. The accuracy of the model is verified by comparing it with experimental values obtained for a GaN-based p-i-n structure under scanning electron microscope illumination.

Model of Ni-63 battery with realistic PIN structure

International Nuclear Information System (INIS)

Munson, Charles E.; Voss, Paul L.; Ougazzaden, Abdallah; Arif, Muhammad; Salvestrini, Jean-Paul; Streque, Jeremy; El Gmili, Youssef; Belahsene, Sofiane; Martinez, Anthony; Ramdane, Abderrahim

2015-01-01

GaN, with its wide bandgap of 3.4 eV, has emerged as an efficient material for designing high-efficiency betavoltaic batteries. An important part of designing efficient betavoltaic batteries involves a good understanding of the full process, from the behavior of the nuclear material and the creation of electron-hole pairs all the way through the collection of photo-generated carriers. This paper presents a detailed model based on Monte Carlo and Silvaco for a GaN-based betavoltaic battery device, modeled after Ni-63 as an energy source. The accuracy of the model is verified by comparing it with experimental values obtained for a GaN-based p-i-n structure under scanning electron microscope illumination

A VRLA battery simulation model

International Nuclear Information System (INIS)

Pascoe, Phillip E.; Anbuky, Adnan H.

2004-01-01

A valve regulated lead acid (VRLA) battery simulation model is an invaluable tool for the standby power system engineer. The obvious use for such a model is to allow the assessment of battery performance. This may involve determining the influence of cells suffering from state of health (SOH) degradation on the performance of the entire string, or the running of test scenarios to ascertain the most suitable battery size for the application. In addition, it enables the engineer to assess the performance of the overall power system. This includes, for example, running test scenarios to determine the benefits of various load shedding schemes. It also allows the assessment of other power system components, either for determining their requirements and/or vulnerabilities. Finally, a VRLA battery simulation model is vital as a stand alone tool for educational purposes. Despite the fundamentals of the VRLA battery having been established for over 100 years, its operating behaviour is often poorly understood. An accurate simulation model enables the engineer to gain a better understanding of VRLA battery behaviour. A system level multipurpose VRLA battery simulation model is presented. It allows an arbitrary battery (capacity, SOH, number of cells and number of strings) to be simulated under arbitrary operating conditions (discharge rate, ambient temperature, end voltage, charge rate and initial state of charge). The model accurately reflects the VRLA battery discharge and recharge behaviour. This includes the complex start of discharge region known as the coup de fouet

A holistic aging model for Li(NiMnCo)O2 based 18650 lithium-ion batteries

Science.gov (United States)

Schmalstieg, Johannes; Käbitz, Stefan; Ecker, Madeleine; Sauer, Dirk Uwe

2014-07-01

Knowledge on lithium-ion battery aging and lifetime estimation is a fundamental aspect for successful market introduction in high-priced goods like electric mobility. This paper illustrates the parameterization of a holistic aging model from accelerated aging tests. More than 60 cells of the same type are tested to analyze different impact factors. In calendar aging tests three temperatures and various SOC are applied to the batteries. For cycle aging tests especially different cycle depths and mean SOC are taken into account. Capacity loss and resistance increase are monitored as functions of time and charge throughput during the tests. From these data physical based functions are obtained, giving a mathematical description of aging. To calculate the stress factors like temperature or voltage, an impedance based electric-thermal model is coupled to the aging model. The model accepts power and current profiles as input, furthermore an ambient air temperature profile can be applied. Various drive cycles and battery management strategies can be tested and optimized using the lifetime prognosis of this tool. With the validation based on different realistic driving profiles and temperatures, a robust foundation is provided.

A method of computer modelling the lithium-ion batteries aging process based on the experimental characteristics

Science.gov (United States)

Czerepicki, A.; Koniak, M.

2017-06-01

The paper presents a method of modelling the processes of aging lithium-ion batteries, its implementation as a computer application and results for battery state estimation. Authors use previously developed behavioural battery model, which was built using battery operating characteristics obtained from the experiment. This model was implemented in the form of a computer program using a database to store battery characteristics. Batteries aging process is a new extended functionality of the model. Algorithm of computer simulation uses a real measurements of battery capacity as a function of the battery charge and discharge cycles number. Simulation allows to take into account the incomplete cycles of charge or discharge battery, which are characteristic for transport powered by electricity. The developed model was used to simulate the battery state estimation for different load profiles, obtained by measuring the movement of the selected means of transport.

Model-based energy analysis of battery powered systems

NARCIS (Netherlands)

Jongerden, M.R.

2010-01-01

The use of mobile devices is often limited by the lifetime of the included batteries. This lifetime naturally depends on the battery's capacity and on the rate at which the battery is discharged. However, it also depends on the usage pattern, i.e., the workload, of the battery. When a battery is

Selection and impedance based model of a lithium ion battery technology for integration with virtual power plant

DEFF Research Database (Denmark)

Swierczynski, Maciej Jozef; Stroe, Daniel Ioan; Stan, Ana-Irina

2013-01-01

is to integrate lithium-ion batteries into virtual power plants; thus, the power system stability and the energy quality can be increased. The selection of the best lithium-ion battery candidate for integration with wind power plants is a key aspect for the economic feasibility of the virtual power plant...... investment. This paper presents a methodology for selection, between three candidates, of a Li-ion battery which offers long cycle lifetime at partial charge/discharge (required by many grid support applications) while providing a low cost per cycle also. For the selected Li-ion battery an impedance......-based diagnostic tool for lifetime estimation was developed and verified. This diagnostic tool can be extended into an impedance-based lifetime model that will be able to predict the remaining useful lifetime of Li-ion batteries for specific grid support applications....

Degradation Behavior of Lithium-Ion Batteries Based on Lifetime Models and Field Measured Frequency Regulation Mission Profile

DEFF Research Database (Denmark)

Stroe, Daniel Loan; Swierczynski, Maciej Jozef; Stroe, Ana-Irina

2016-01-01

Energy storage systems based on Lithium-ion (Li-ion) batteries have been proposed as an environmentally friendly alternative to traditional conventional generating units for providing grid frequency regulation. One major challenge regarding the use of Lithium-ion batteries in such applications...... is their higher cost—in comparison with other storage technologies or with the traditional frequency regulation methods—combined with performance-degradation uncertainties. In order to surpass this challenge and to allow for optimal sizing and proper operation of the battery, accurate knowledge about the lifetime...... of the Li-ion battery and its degradation behavior is required. Thus, this paper aims to investigate, based on a laboratory developed lifetime model, the degradation behavior of the performance parameters (i.e., capacity and power capability) of a Li-ion battery cell when it is subjected to a field measured...

Li-NMC Batteries Model Evaluation with Experimental Data for Electric Vehicle Application

Directory of Open Access Journals (Sweden)

Aleksandra Baczyńska

2018-02-01

Full Text Available The aim of the paper is to present the battery equivalent circuit for electric vehicle application. Moreover, the model described below is dedicated to lithium-ion types of batteries. The purpose of this paper is to introduce an efficient and transparent method to develop a battery equivalent circuit model. Battery modeling requires, depending on the chosen method, either significant calculations or a highly developed mathematical model for optimization. The model is evaluated in comparison to the real data measurements, to present the performance of the method. Battery measurements based on charge/discharge tests at a fixed C-rate are presented to show the relation of the output voltage profiles with the battery state of charge. The pulse discharge test is presented to obtain the electric parameters of the battery equivalent circuit model, using a Thévenin circuit. According to the Reverse Trike Ecologic Electric Vehicle (VEECO RT characteristics used as a case study in this work, new values for vehicle autonomy and battery pack volume based on lithium nickel manganese cobalt oxide cells are evaluated.

A Capacity Fading Model of Lithium-Ion Battery Cycle Life Based on the Kinetics of Side Reactions for Electric Vehicle Applications

International Nuclear Information System (INIS)

Gu, Weijun; Sun, Zechang; Wei, Xuezhe; Dai, Haifeng

2014-01-01

Highlights: • Describe the aging mechanism of lithium-ion battery with electrochemical kinetics. • Establish the fading rate equation based on Eyring Equation. • The established equation is applicable to any reaction order. • Integrate the internal kinetics with external degradation characteristics. - Abstract: Battery life prediction is one of the critical issues that restrict the development of electric vehicles. Among the typical battery life models, the mechanism model focusing on the internal physical or electrochemical processes has a stronger theoretical foundation and greater accuracy. The empirical formula, which relies on the simplified mechanism, has a concise model structure and more flexibility in vehicle applications. However, the internal aging mechanism rarely correlates with the external operating characteristics. Based on the summary of the capacity fading mechanism and the reasoning of the internal kinetics of side reactions during the aging process, a lifetime model of the lithium-ion battery is established in this paper. The solutions to the vital parameters based on the external accelerated life testing results are also presented. The testing sample is a manganese oxide lithium-ion battery of 8 Ah. The validation results indicated that the life model established in this paper can describe the capacity fading law of the lithium-ion battery and the operability and accuracy for vehicle applications

Model-based fault diagnosis approach on external short circuit of lithium-ion battery used in electric vehicles

International Nuclear Information System (INIS)

Chen, Zeyu; Xiong, Rui; Tian, Jinpeng; Shang, Xiong; Lu, Jiahuan

2016-01-01

Highlights: • The characteristics of ESC fault of lithium-ion battery are investigated experimentally. • The proposed method to simulate the electrical behavior of ESC fault is viable. • Ten parameters in the presented fault model were optimized using a DPSO algorithm. • A two-layer model-based fault diagnosis approach for battery ESC is proposed. • The effective and robustness of the proposed algorithm has been evaluated. - Abstract: This study investigates the external short circuit (ESC) fault characteristics of lithium-ion battery experimentally. An experiment platform is established and the ESC tests are implemented on ten 18650-type lithium cells considering different state-of-charges (SOCs). Based on the experiment results, several efforts have been made. (1) The ESC process can be divided into two periods and the electrical and thermal behaviors within these two periods are analyzed. (2) A modified first-order RC model is employed to simulate the electrical behavior of the lithium cell in the ESC fault process. The model parameters are re-identified by a dynamic-neighborhood particle swarm optimization algorithm. (3) A two-layer model-based ESC fault diagnosis algorithm is proposed. The first layer conducts preliminary fault detection and the second layer gives a precise model-based diagnosis. Four new cells are short-circuited to evaluate the proposed algorithm. It shows that the ESC fault can be diagnosed within 5 s, the error between the model and measured data is less than 0.36 V. The effectiveness of the fault diagnosis algorithm is not sensitive to the precision of battery SOC. The proposed algorithm can still make the correct diagnosis even if there is 10% error in SOC estimation.

A dynamic model-based estimate of the value of a vanadium redox flow battery for frequency regulation in Texas

International Nuclear Information System (INIS)

Fares, Robert L.; Meyers, Jeremy P.; Webber, Michael E.

2014-01-01

Highlights: • A model is implemented to describe the dynamic voltage of a vanadium flow battery. • The model is used with optimization to maximize the utility of the battery. • A vanadium flow battery’s value for regulation service is approximately $1500/kW. - Abstract: Building on past work seeking to value emerging energy storage technologies in grid-based applications, this paper introduces a dynamic model-based framework to value a vanadium redox flow battery (VRFB) participating in Texas’ organized electricity market. Our model describes the dynamic behavior of a VRFB system’s voltage and state of charge based on the instantaneous charging or discharging power required from the battery. We formulate an optimization problem that incorporates the model to show the potential value of a VRFB used for frequency regulation service in Texas. The optimization is implemented in Matlab using the large-scale, interior-point, nonlinear optimization algorithm, with the objective function gradient, nonlinear constraint gradients, and Hessian matrix specified analytically. Utilizing market prices and other relevant data from the Electric Reliability Council of Texas (ERCOT), we find that a VRFB system used for frequency regulation service could be worth approximately $1500/kW

Battery Performance Modelling ad Simulation: a Neural Network Based Approach

Science.gov (United States)

Ottavianelli, Giuseppe; Donati, Alessandro

2002-01-01

This project has developed on the background of ongoing researches within the Control Technology Unit (TOS-OSC) of the Special Projects Division at the European Space Operations Centre (ESOC) of the European Space Agency. The purpose of this research is to develop and validate an Artificial Neural Network tool (ANN) able to model, simulate and predict the Cluster II battery system's performance degradation. (Cluster II mission is made of four spacecraft flying in tetrahedral formation and aimed to observe and study the interaction between sun and earth by passing in and out of our planet's magnetic field). This prototype tool, named BAPER and developed with a commercial neural network toolbox, could be used to support short and medium term mission planning in order to improve and maximise the batteries lifetime, determining which are the future best charge/discharge cycles for the batteries given their present states, in view of a Cluster II mission extension. This study focuses on the five Silver-Cadmium batteries onboard of Tango, the fourth Cluster II satellite, but time restrains have allowed so far to perform an assessment only on the first battery. In their most basic form, ANNs are hyper-dimensional curve fits for non-linear data. With their remarkable ability to derive meaning from complicated or imprecise history data, ANN can be used to extract patterns and detect trends that are too complex to be noticed by either humans or other computer techniques. ANNs learn by example, and this is why they can be described as an inductive, or data-based models for the simulation of input/target mappings. A trained ANN can be thought of as an "expert" in the category of information it has been given to analyse, and this expert can then be used, as in this project, to provide projections given new situations of interest and answer "what if" questions. The most appropriate algorithm, in terms of training speed and memory storage requirements, is clearly the Levenberg

A mass transfer based variable porosity model with particle radius change for a Lithium-ion battery

International Nuclear Information System (INIS)

Ashwin, T.R.; McGordon, A.; Jennings, P.A.

2017-01-01

Highlights: • Mass transfer based model to calculate the porosity variation and radius change. • Can be used with any model that calculates Lithium concentration in electrolyte. • Considers SEI as a mass deposition rather than simply an internal resistance. • Brings more accuracy to the volume specific area and the Butler-Volmer kinetics • Practical applicability in pre-lithiation, lithium plating and stress calculation. - Abstract: Micro pore-clogging in the electrodes due to SEI growth and other side reactions can cause adverse effects on the performance of a Lithium-ion battery. The fundamental problem of volume fraction variation and particle radius change during the charge-discharge process in a lithium-ion battery is modelled in this paper with the help of mass transfer based formulation and demonstrated on a battery with LiCoO_2 chemistry. The model can handle the volume fraction change due to intercalation reaction, solvent reduction side reaction and the electrolyte density change due to side reaction contamination in the battery. The entire calculation presented in this paper models particle radius and volume fraction together and therefore gives greater accuracy in calculating the volume-specific-area of the reacting particles which is an important parameter controlling the Butler-Volmer kinetics. The mass deposit on the electrode (or loss of lithium) gives an indication of the amount of pre-lithiation required to maintain cell performance while the amount of mass deposited on the SEI helps to decide the safe operating condition for which the clogging of pores and capacity fade will be minimal. Moreover the model presented in this paper has wide applicability in analysing the stress development inside the battery due to irreversible porous filling.

Hybrid unscented particle filter based state-of-charge determination for lead-acid batteries

International Nuclear Information System (INIS)

Shen, Yanqing

2014-01-01

Accurate prediction of cell SOC (state of charge) is important for the safety and functional capabilities of the battery energy storage application system. This paper presents a hybrid UPF (unscented particle filter) based SOC determination combined model for batteries. To simulate the entire dynamic electrical characteristics of batteries, a novel combined state space model, which takes current as a control input and let SOC and two constructed parameters as state variables, is advanced to represent cell behavior. Besides that, an improved UPF method is used to evaluate cell SOC. Taking lead-acid batteries for example, we apply the established model for test. Results show that the evolved combined state space cell model simulates battery dynamics robustly with high accuracy and the prediction value based on the improved UPF method converges to the real SOC very quickly within the error of±2%. - Highlights: • This paper introduces a hybrid UPF based SOC determination model for batteries. • The evolved model takes SOC and two constructed parameters as state variables. • The combined state space cell model simulates battery dynamics robustly. • NLMS based method is employed to lessen search space and fasten convergence process. • Novel model converges to the real SOC robustly and quickly with fewer particles

Comparison Study on Two Model-Based Adaptive Algorithms for SOC Estimation of Lithium-Ion Batteries in Electric Vehicles

Directory of Open Access Journals (Sweden)

Yong Tian

2014-12-01

Full Text Available State of charge (SOC estimation is essential to battery management systems in electric vehicles (EVs to ensure the safe operations of batteries and providing drivers with the remaining range of the EVs. A number of estimation algorithms have been developed to get an accurate SOC value because the SOC cannot be directly measured with sensors and is closely related to various factors, such as ambient temperature, current rate and battery aging. In this paper, two model-based adaptive algorithms, including the adaptive unscented Kalman filter (AUKF and adaptive slide mode observer (ASMO are applied and compared in terms of convergence behavior, tracking accuracy, computational cost and estimation robustness against parameter uncertainties of the battery model in SOC estimation. Two typical driving cycles, including the Dynamic Stress Test (DST and New European Driving Cycle (NEDC are applied to evaluate the performance of the two algorithms. Comparison results show that the AUKF has merits in convergence ability and tracking accuracy with an accurate battery model, while the ASMO has lower computational cost and better estimation robustness against parameter uncertainties of the battery model.

Models for Battery Reliability and Lifetime

Energy Technology Data Exchange (ETDEWEB)

Smith, K.; Wood, E.; Santhanagopalan, S.; Kim, G. H.; Neubauer, J.; Pesaran, A.

2014-03-01

Models describing battery degradation physics are needed to more accurately understand how battery usage and next-generation battery designs can be optimized for performance and lifetime. Such lifetime models may also reduce the cost of battery aging experiments and shorten the time required to validate battery lifetime. Models for chemical degradation and mechanical stress are reviewed. Experimental analysis of aging data from a commercial iron-phosphate lithium-ion (Li-ion) cell elucidates the relative importance of several mechanical stress-induced degradation mechanisms.

Adaptive estimation of state of charge and capacity with online identified battery model for vanadium redox flow battery

Science.gov (United States)

Wei, Zhongbao; Tseng, King Jet; Wai, Nyunt; Lim, Tuti Mariana; Skyllas-Kazacos, Maria

2016-11-01

Reliable state estimate depends largely on an accurate battery model. However, the parameters of battery model are time varying with operating condition variation and battery aging. The existing co-estimation methods address the model uncertainty by integrating the online model identification with state estimate and have shown improved accuracy. However, the cross interference may arise from the integrated framework to compromise numerical stability and accuracy. Thus this paper proposes the decoupling of model identification and state estimate to eliminate the possibility of cross interference. The model parameters are online adapted with the recursive least squares (RLS) method, based on which a novel joint estimator based on extended Kalman Filter (EKF) is formulated to estimate the state of charge (SOC) and capacity concurrently. The proposed joint estimator effectively compresses the filter order which leads to substantial improvement in the computational efficiency and numerical stability. Lab scale experiment on vanadium redox flow battery shows that the proposed method is highly authentic with good robustness to varying operating conditions and battery aging. The proposed method is further compared with some existing methods and shown to be superior in terms of accuracy, convergence speed, and computational cost.

Neural Network Modeling of the Lithium/Thionyl Chloride Battery System

Energy Technology Data Exchange (ETDEWEB)

Ingersoll, D.; Jungst, R.G.; O' Gorman, C.C.; Paez, T.L.

1998-10-29

Battery systems have traditionally relied on extensive build and test procedures for product realization. Analytical models have been developed to diminish this reliance, but have only been partially successful in consistently predicting the performance of battery systems. The complex set of interacting physical and chemical processes within battery systems has made the development of analytical models a significant challenge. Advanced simulation tools are needed to more accurately model battery systems which will reduce the time and cost required for product realization. Sandia has initiated an advanced model-based design strategy to battery systems, beginning with the performance of lithiumhhionyl chloride cells. As an alternative approach, we have begun development of cell performance modeling using non-phenomenological models for battery systems based on artificial neural networks (ANNs). ANNs are inductive models for simulating input/output mappings with certain advantages over phenomenological models, particularly for complex systems. Among these advantages is the ability to avoid making measurements of hard to determine physical parameters or having to understand cell processes sufficiently to write mathematical functions describing their behavior. For example, ANN models are also being studied for simulating complex physical processes within the Li/SOC12 cell, such as the time and temperature dependence of the anode interracial resistance. ANNs have been shown to provide a very robust and computationally efficient simulation tool for predicting voltage and capacity output for Li/SOC12 cells under a variety of operating conditions. The ANN modeling approach should be applicable to a wide variety of battery chemistries, including rechargeable systems.

Development of efficient air-cooling strategies for lithium-ion battery module based on empirical heat source model

International Nuclear Information System (INIS)

Wang, Tao; Tseng, K.J.; Zhao, Jiyun

2015-01-01

Thermal modeling is the key issue in thermal management of lithium-ion battery system, and cooling strategies need to be carefully investigated to guarantee the temperature of batteries in operation within a narrow optimal range as well as provide cost effective and energy saving solutions for cooling system. This article reviews and summarizes the past cooling methods especially forced air cooling and introduces an empirical heat source model which can be widely applied in the battery module/pack thermal modeling. In the development of empirical heat source model, three-dimensional computational fluid dynamics (CFD) method is employed, and thermal insulation experiments are conducted to provide the key parameters. A transient thermal model of 5 × 5 battery module with forced air cooling is then developed based on the empirical heat source model. Thermal behaviors of battery module under different air cooling conditions, discharge rates and ambient temperatures are characterized and summarized. Varies cooling strategies are simulated and compared in order to obtain an optimal cooling method. Besides, the battery fault conditions are predicted from transient simulation scenarios. The temperature distributions and variations during discharge process are quantitatively described, and it is found that the upper limit of ambient temperature for forced air cooling is 35 °C, and when ambient temperature is lower than 20 °C, forced air-cooling is not necessary. - Highlights: • An empirical heat source model is developed for battery thermal modeling. • Different air-cooling strategies on module thermal characteristics are investigated. • Impact of different discharge rates on module thermal responses are investigated. • Impact of ambient temperatures on module thermal behaviors are investigated. • Locations of maximum temperatures under different operation conditions are studied.

A Simple theoretical model for 63Ni betavoltaic battery

International Nuclear Information System (INIS)

ZUO, Guoping; ZHOU, Jianliang; KE, Guotu

2013-01-01

A numerical simulation of the energy deposition distribution in semiconductors is performed for 63 Ni beta particles. Results show that the energy deposition distribution exhibits an approximate exponential decay law. A simple theoretical model is developed for 63 Ni betavoltaic battery based on the distribution characteristics. The correctness of the model is validated by two literature experiments. Results show that the theoretical short-circuit current agrees well with the experimental results, and the open-circuit voltage deviates from the experimental results in terms of the influence of the PN junction defects and the simplification of the source. The theoretical model can be applied to 63 Ni and 147 Pm betavoltaic batteries. - Highlights: • The energy deposition distribution is found following an approximate exponential decay law when beta particles emitted from 63 Ni pass through a semiconductor. • A simple theoretical model for 63 Ni betavoltaic battery is constructed based on the exponential decay law. • Theoretical model can be applied to the betavoltaic batteries which radioactive source has a similar energy spectrum with 63 Ni, such as 147 Pm

Modeling aluminum-air battery systems

Science.gov (United States)

Savinell, R. F.; Willis, M. S.

The performance of a complete aluminum-air battery system was studied with a flowsheet model built from unit models of each battery system component. A plug flow model for heat transfer was used to estimate the amount of heat transferred from the electrolyte to the air stream. The effect of shunt currents on battery performance was found to be insignificant. Using the flowsheet simulator to analyze a 100 cell battery system now under development demonstrated that load current, aluminate concentration, and electrolyte temperature are dominant variables controlling system performance. System efficiency was found to decrease as both load current and aluminate concentration increases. The flowsheet model illustrates the interdependence of separate units on overall system performance.

Electrochemical Model for Ionic Liquid Electrolytes in Lithium Batteries

International Nuclear Information System (INIS)

Yoo, Kisoo; Deshpande, Anirudh; Banerjee, Soumik; Dutta, Prashanta

2015-01-01

ABSTRACT: Room temperature ionic liquids are considered as potential electrolytes for high performance and safe lithium batteries due to their very low vapor pressure and relatively wide electrochemical and thermal stability windows. Unlike organic electrolytes, ionic liquid electrolytes are molten salts at room temperature with dissociated cations and anions. These dissociated ions interfere with the transport of lithium ions in lithium battery. In this study, a mathematical model is developed for transport of ionic components to study the performance of ionic liquid based lithium batteries. The mathematical model is based on a univalent ternary electrolyte frequently encountered in ionic liquid electrolytes of lithium batteries. Owing to the very high concentration of components in ionic liquid, the transport of lithium ions is described by the mutual diffusion phenomena using Maxwell-Stefan diffusivities, which are obtained from atomistic simulation. The model is employed to study a lithium-ion battery where the electrolyte comprises ionic liquid with mppy + (N-methyl-N-propyl pyrrolidinium) cation and TFSI − (bis trifluoromethanesulfonyl imide) anion. For a moderate value of reaction rate constant, the electric performance results predicted by the model are in good agreement with experimental data. We also studied the effect of porosity and thickness of separator on the performance of lithium-ion battery using this model. Numerical results indicate that low rate of lithium ion transport causes lithium depleted zone in the porous cathode regions as the porosity decreases or the length of the separator increases. The lithium depleted region is responsible for lower specific capacity in lithium-ion cells. The model presented in this study can be used for design of optimal ionic liquid electrolytes for lithium-ion and lithium-air batteries

Model-based energy analysis of battery powered systems

NARCIS (Netherlands)

Jongerden, M.R.

2010-01-01

The use of mobile devices is often limited by the lifetime of the included batteries. This lifetime naturally depends on the battery’s capacity and on the rate at which the battery is discharged. However, it also depends on the usage pattern, i.e., the workload, of the battery. When a battery is

Battery sizing for serial plug-in hybrid electric vehicles: A model-based economic analysis for Germany

International Nuclear Information System (INIS)

Ernst, Christian-Simon; Hackbarth, Andre; Madlener, Reinhard; Lunz, Benedikt; Uwe Sauer, Dirk; Eckstein, Lutz

2011-01-01

The battery size of a Plug-in Hybrid Electric Vehicle (PHEV) is decisive for the electrical range of the vehicle and crucial for the cost-effectiveness of this particular vehicle concept. Based on the energy consumption of a conventional reference car and a PHEV, we introduce a comprehensive total cost of ownership model for the average car user in Germany for both vehicle types. The model takes into account the purchase price, fixed annual costs and variable operating costs. The amortization time of a PHEV also depends on the recharging strategy (once a day, once a night, after each trip), the battery size, and the battery costs. We find that PHEVs with a 4 kWh battery and at current lithium-ion battery prices reach the break-even point after about 6 years (5 years when using the lower night-time electricity tariffs). With higher battery capacities the amortization time becomes significantly longer. Even for the small battery size and assuming the EU-15 electricity mix, a PHEV is found to emit only around 60% of the CO 2 emissions of a comparable conventional car. Thus, with the PHEV concept a cost-effective introduction of electric mobility and reduction of greenhouse gas emissions per vehicle can be reached. - Highlights: → Total cost of ownership of a PHEV and a conventional car are compared for the average German car user.→ PHEVs with a 4 kWh battery reach the break-even after 5-6 years at current Li-Ion battery prices.→ Even with a small battery, PHEVs emit about 40% less CO 2 emissions than the average conventional car.

Techno-Economic Modeling and Analysis of Redox Flow Battery Systems

Directory of Open Access Journals (Sweden)

Jens Noack

2016-08-01

Full Text Available A techno-economic model was developed to investigate the influence of components on the system costs of redox flow batteries. Sensitivity analyses were carried out based on an example of a 10 kW/120 kWh vanadium redox flow battery system, and the costs of the individual components were analyzed. Particular consideration was given to the influence of the material costs and resistances of bipolar plates and energy storage media as well as voltages and electric currents. Based on the developed model, it was possible to formulate statements about the targeted optimization of a developed non-commercial vanadium redox flow battery system and general aspects for future developments of redox flow batteries.

Enhanced Prognostic Model for Lithium Ion Batteries Based on Particle Filter State Transition Model Modification

Directory of Open Access Journals (Sweden)

Buddhi Arachchige

2017-11-01

Full Text Available This paper focuses on predicting the End of Life and End of Discharge of Lithium ion batteries using a battery capacity fade model and a battery discharge model. The proposed framework will be able to estimate the Remaining Useful Life (RUL and the Remaining charge through capacity fade and discharge models. A particle filter is implemented that estimates the battery’s State of Charge (SOC and State of Life (SOL by utilizing the battery’s physical data such as voltage, temperature, and current measurements. The accuracy of the prognostic framework has been improved by enhancing the particle filter state transition model to incorporate different environmental and loading conditions without retuning the model parameters. The effect of capacity fade in the reduction of the EOD (End of Discharge time with cycling has also been included, integrating both EOL (End of Life and EOD prediction models in order to get more accuracy in the estimations.

Non-destructive fast charging algorithm of lithium-ion batteries based on the control-oriented electrochemical model

International Nuclear Information System (INIS)

Chu, Zhengyu; Feng, Xuning; Lu, Languang; Li, Jianqiu; Han, Xuebing; Ouyang, Minggao

2017-01-01

Highlights: •A novel non-destructive fast charging algorithm of lithium-ion batteries is proposed. •A close-loop observer of lithium deposition status is constructed based on the SP2D model. •The charging current is modified online using the feedback of the lithium deposition status. •The algorithm can shorten the charging time and can be used for charging from different initial SOCs. •The post-mortem observation and degradation tests show that no lithium deposition occurs during fast charging. -- Abstract: Fast charging is critical for the application of lithium-ion batteries in electric vehicles. Conventional fast charging algorithms may shorten the cycle life of lithium-ion batteries and induce safety problems, such as internal short circuit caused by lithium deposition at the negative electrode. In this paper, a novel, non-destructive model-based fast charging algorithm is proposed. The fast charging algorithm is composed of two closed loops. The first loop includes an anode over-potential observer that can observe the status of lithium deposition online, whereas the second loop includes a feedback structure that can modify the current based on the observed status of lithium deposition. The charging algorithm enhances the charging current to maintain the observed anode over-potential near the preset threshold potential. Therefore, the fast charging algorithm can decrease the charging time while protecting the health of the battery. The fast charging algorithm is validated on a commercial large-format nickel cobalt manganese/graphite cell. The results showed that 96.8% of the battery capacity can be charged within 52 min. The post-mortem observation of the surface of the negative electrode and degradation tests revealed that the fast charging algorithm proposed here protected the battery from lithium deposition.

Overview of Lithium-Ion Battery Modeling Methods for State-of-Charge Estimation in Electrical Vehicles

DEFF Research Database (Denmark)

Jinhao, Meng; Guangzhao, Luo; Ricco, Mattia

2018-01-01

As a critical indictor in the Battery Management System (BMS), State of Charge (SOC) is closely related to the reliable and safe operation of lithium-ion (Li-ion) batteries. Model-based methods are an effective solution for accurate and robust SOC estimation, the performance of which heavily relies...... on the battery model. This paper mainly focuses on battery modeling methods, which have the potential to be used in a model-based SOC estimation structure. Battery modeling methods are classified into four categories on the basis of their theoretical foundations, and their expressions and features are detailed....... Furthermore, the four battery modeling methods are compared in terms of their pros and cons. Future research directions are also presented. In addition, after optimizing the parameters of the battery models by a Genetic Algorithm (GA), four typical battery models including a combined model, two RC Equivalent...

Online model-based estimation of state-of-charge and open-circuit voltage of lithium-ion batteries in electric vehicles

International Nuclear Information System (INIS)

He, Hongwen; Zhang, Xiaowei; Xiong, Rui; Xu, Yongli; Guo, Hongqiang

2012-01-01

This paper presents a method to estimate the state-of-charge (SOC) of a lithium-ion battery, based on an online identification of its open-circuit voltage (OCV), according to the battery’s intrinsic relationship between the SOC and the OCV for application in electric vehicles. Firstly an equivalent circuit model with n RC networks is employed modeling the polarization characteristic and the dynamic behavior of the lithium-ion battery, the corresponding equations are built to describe its electric behavior and a recursive function is deduced for the online identification of the OCV, which is implemented by a recursive least squares (RLS) algorithm with an optimal forgetting factor. The models with different RC networks are evaluated based on the terminal voltage comparisons between the model-based simulation and the experiment. Then the OCV-SOC lookup table is built based on the experimental data performed by a linear interpolation of the battery voltages at the same SOC during two consecutive discharge and charge cycles. Finally a verifying experiment is carried out based on nine Urban Dynamometer Driving Schedules. It indicates that the proposed method can ensure an acceptable accuracy of SOC estimation for online application with a maximum error being less than 5.0%. -- Highlights: ► An equivalent circuit model with n RC networks is built for lithium-ion batteries. ► A recursive function is deduced for the online estimation of the model parameters like OCV and R O . ► The relationship between SOC and OCV is built with a linear interpolation method by experiments. ► The experiments show the online model-based SOC estimation is reasonable with enough accuracy.

Modeling Battery Behavior on Sensory Operations for Context-Aware Smartphone Sensing

OpenAIRE

Yurur, Ozgur; Liu, Chi Harold; Moreno, Wilfrido

2015-01-01

Energy consumption is a major concern in context-aware smartphone sensing. This paper first studies mobile device-based battery modeling, which adopts the kinetic battery model (KiBaM), under the scope of battery non-linearities with respect to variant loads. Second, this paper models the energy consumption behavior of accelerometers analytically and then provides extensive simulation results and a smartphone application to examine the proposed sensor model. Third, a Markov reward process is ...

Identification and modelling of Lithium ion battery

International Nuclear Information System (INIS)

Tsang, K.M.; Sun, L.; Chan, W.L.

2010-01-01

A universal battery model for the charging process has been identified for Lithium ion battery working at constant temperature. Mathematical models are fitted to different collected charging profiles using the least squares algorithm. With the removal of the component which is related to the DC resistance of the battery, a universal model can be fitted to predict profiles of different charging rates after time scaling. Experimental results are included to demonstrate the goodness of fit of the model at different charging rates and for batteries of different capacities. Comparison with standard electrical-circuit model is also presented. With the proposed model, it is possible to derive more effective way to monitor the status of Lithium ion batteries, and to develop a universal quick charger for different capacities of batteries to result with a more effective usage of Lithium ion batteries.

Impedance-based overcharging and gassing model for VRLA/AGM batteries

Science.gov (United States)

Thele, M.; Karden, E.; Surewaard, E.; Sauer, D. U.

This paper presents for the first time an impedance-based non-linear model for lead-acid batteries that is applicable in all operational modes. An overcharging model describes the accumulation and depletion of the dissolved Pb 2+ ions. This physical model has been added to the earlier presented model to expand the model validity. To properly represent the charge acceptance during dynamic operation, a concept of "hardening crystals" has been introduced in the model. Moreover, a detailed gassing and oxygen recombination model has been integrated. A realistic simulation of the overcharging behavior is now possible. The mathematical description is given in the paper. Simplifications are introduced that allow for an efficient implementation and for model parameterization in the time domain. A comparison between experimental data and simulation results demonstrates the achieved accuracy. The model enhancement is of major importance to analyze charging strategies especially in partial-cycling operation with limited charging time, e.g. in electrically assisted or hybrid cars and autonomous power supply systems.

Strain measurement based battery testing

Science.gov (United States)

Xu, Jeff Qiang; Steiber, Joe; Wall, Craig M.; Smith, Robert; Ng, Cheuk

2017-05-23

A method and system for strain-based estimation of the state of health of a battery, from an initial state to an aged state, is provided. A strain gauge is applied to the battery. A first strain measurement is performed on the battery, using the strain gauge, at a selected charge capacity of the battery and at the initial state of the battery. A second strain measurement is performed on the battery, using the strain gauge, at the selected charge capacity of the battery and at the aged state of the battery. The capacity degradation of the battery is estimated as the difference between the first and second strain measurements divided by the first strain measurement.

Modeling charge polarization voltage for large lithium-ion batteries in electric vehicles

Directory of Open Access Journals (Sweden)

Yan Jiang

2013-06-01

Full Text Available Purpose: Polarization voltage of the lithium-ion battery is an important parameter that has direct influence on battery performance. The paper aims to analyze the impedance characteristics of the lithium-ion battery based on EIS data. Design/methodology/approach: The effects of currents, initial SOC of the battery on charge polarization voltage are investigated, which is approximately linear function of charge current. The change of charge polarization voltage is also analyzed with the gradient analytical method in the SOC domain. The charge polarization model with two RC networks is presented, and parts of model parameters like Ohmic resistance and charge transfer impedance are estimated by both EIS method and battery constant current testing method. Findings: This paper reveals that the Ohmic resistance accounts for much contribution to battery total polarization compared to charge transfer impedance. Practical implications: Experimental results demonstrate the efficacy of the model with the proposed identification method, which provides the foundation for battery charging optimization. Originality/value: The paper analyzed the impedance characteristics of the lithium-ion battery based on EIS data, presented a charge polarization model with two RC networks, and estimated parameters like Ohmic resistance and charge transfer impedance.

Co-estimation of state-of-charge, capacity and resistance for lithium-ion batteries based on a high-fidelity electrochemical model

International Nuclear Information System (INIS)

Zheng, Linfeng; Zhang, Lei; Zhu, Jianguo; Wang, Guoxiu; Jiang, Jiuchun

2016-01-01

Highlights: • The numerical solution for an electrochemical model is presented. • Trinal PI observers are used to concurrently estimate SOC, capacity and resistance. • An iteration-approaching method is incorporated to enhance estimation performance. • The robustness against aging and temperature variations is experimentally verified. - Abstract: Lithium-ion batteries have been widely used as enabling energy storage in many industrial fields. Accurate modeling and state estimation play fundamental roles in ensuring safe, reliable and efficient operation of lithium-ion battery systems. A physics-based electrochemical model (EM) is highly desirable for its inherent ability to push batteries to operate at their physical limits. For state-of-charge (SOC) estimation, the continuous capacity fade and resistance deterioration are more prone to erroneous estimation results. In this paper, trinal proportional-integral (PI) observers with a reduced physics-based EM are proposed to simultaneously estimate SOC, capacity and resistance for lithium-ion batteries. Firstly, a numerical solution for the employed model is derived. PI observers are then developed to realize the co-estimation of battery SOC, capacity and resistance. The moving-window ampere-hour counting technique and the iteration-approaching method are also incorporated for the estimation accuracy improvement. The robustness of the proposed approach against erroneous initial values, different battery cell aging levels and ambient temperatures is systematically evaluated, and the experimental results verify the effectiveness of the proposed method.

Simulation of Ni-63 based nuclear micro battery using Monte Carlo modeling

International Nuclear Information System (INIS)

Kim, Tae Ho; Kim, Ji Hyun

2013-01-01

The radioisotope batteries have an energy density of 100-10000 times greater than chemical batteries. Also, Li ion battery has the fundamental problems such as short life time and requires recharge system. In addition to these things, the existing batteries are hard to operate at internal human body, national defense arms or space environment. Since the development of semiconductor process and materials technology, the micro device is much more integrated. It is expected that, based on new semiconductor technology, the conversion device efficiency of betavoltaic battery will be highly increased. Furthermore, the radioactivity from the beta particle cannot penetrate a skin of human body, so it is safer than Li battery which has the probability to explosion. In the other words, the interest for radioisotope battery is increased because it can be applicable to an artificial internal organ power source without recharge and replacement, micro sensor applied to arctic and special environment, small size military equipment and space industry. However, there is not enough data for beta particle fluence from radioisotope source using nuclear battery. Beta particle fluence directly influences on battery efficiency and it is seriously affected by radioisotope source thickness because of self-absorption effect. Therefore, in this article, we present a basic design of Ni-63 nuclear battery and simulation data of beta particle fluence with various thickness of radioisotope source and design of battery

Modeling Battery Behavior on Sensory Operations for Context-Aware Smartphone Sensing

Directory of Open Access Journals (Sweden)

Ozgur Yurur

2015-05-01

Full Text Available Energy consumption is a major concern in context-aware smartphone sensing. This paper first studies mobile device-based battery modeling, which adopts the kinetic battery model (KiBaM, under the scope of battery non-linearities with respect to variant loads. Second, this paper models the energy consumption behavior of accelerometers analytically and then provides extensive simulation results and a smartphone application to examine the proposed sensor model. Third, a Markov reward process is integrated to create energy consumption profiles, linking with sensory operations and their effects on battery non-linearity. Energy consumption profiles consist of different pairs of duty cycles and sampling frequencies during sensory operations. Furthermore, the total energy cost by each profile is represented by an accumulated reward in this process. Finally, three different methods are proposed on the evolution of the reward process, to present the linkage between different usage patterns on the accelerometer sensor through a smartphone application and the battery behavior. By doing this, this paper aims at achieving a fine efficiency in power consumption caused by sensory operations, while maintaining the accuracy of smartphone applications based on sensor usages. More importantly, this study intends that modeling the battery non-linearities together with investigating the effects of different usage patterns in sensory operations in terms of the power consumption and the battery discharge may lead to discovering optimal energy reduction strategies to extend the battery lifetime and help a continual improvement in context-aware mobile services.

Modeling battery behavior on sensory operations for context-aware smartphone sensing.

Science.gov (United States)

Yurur, Ozgur; Liu, Chi Harold; Moreno, Wilfrido

2015-05-26

Energy consumption is a major concern in context-aware smartphone sensing. This paper first studies mobile device-based battery modeling, which adopts the kinetic battery model (KiBaM), under the scope of battery non-linearities with respect to variant loads. Second, this paper models the energy consumption behavior of accelerometers analytically and then provides extensive simulation results and a smartphone application to examine the proposed sensor model. Third, a Markov reward process is integrated to create energy consumption profiles, linking with sensory operations and their effects on battery non-linearity. Energy consumption profiles consist of different pairs of duty cycles and sampling frequencies during sensory operations. Furthermore, the total energy cost by each profile is represented by an accumulated reward in this process. Finally, three different methods are proposed on the evolution of the reward process, to present the linkage between different usage patterns on the accelerometer sensor through a smartphone application and the battery behavior. By doing this, this paper aims at achieving a fine efficiency in power consumption caused by sensory operations, while maintaining the accuracy of smartphone applications based on sensor usages. More importantly, this study intends that modeling the battery non-linearities together with investigating the effects of different usage patterns in sensory operations in terms of the power consumption and the battery discharge may lead to discovering optimal energy reduction strategies to extend the battery lifetime and help a continual improvement in context-aware mobile services.

Physics based modeling of a series parallel battery pack for asymmetry analysis, predictive control and life extension

Science.gov (United States)

Ganesan, Nandhini; Basu, Suman; Hariharan, Krishnan S.; Kolake, Subramanya Mayya; Song, Taewon; Yeo, Taejung; Sohn, Dong Kee; Doo, Seokgwang

2016-08-01

Lithium-Ion batteries used for electric vehicle applications are subject to large currents and various operation conditions, making battery pack design and life extension a challenging problem. With increase in complexity, modeling and simulation can lead to insights that ensure optimal performance and life extension. In this manuscript, an electrochemical-thermal (ECT) coupled model for a 6 series × 5 parallel pack is developed for Li ion cells with NCA/C electrodes and validated against experimental data. Contribution of the cathode to overall degradation at various operating conditions is assessed. Pack asymmetry is analyzed from a design and an operational perspective. Design based asymmetry leads to a new approach of obtaining the individual cell responses of the pack from an average ECT output. Operational asymmetry is demonstrated in terms of effects of thermal gradients on cycle life, and an efficient model predictive control technique is developed. Concept of reconfigurable battery pack is studied using detailed simulations that can be used for effective monitoring and extension of battery pack life.

Sequential Monte Carlo filter for state estimation of LiFePO4 batteries based on an online updated model

Science.gov (United States)

Li, Jiahao; Klee Barillas, Joaquin; Guenther, Clemens; Danzer, Michael A.

2014-02-01

Battery state monitoring is one of the key techniques in battery management systems e.g. in electric vehicles. An accurate estimation can help to improve the system performance and to prolong the battery remaining useful life. Main challenges for the state estimation for LiFePO4 batteries are the flat characteristic of open-circuit-voltage over battery state of charge (SOC) and the existence of hysteresis phenomena. Classical estimation approaches like Kalman filtering show limitations to handle nonlinear and non-Gaussian error distribution problems. In addition, uncertainties in the battery model parameters must be taken into account to describe the battery degradation. In this paper, a novel model-based method combining a Sequential Monte Carlo filter with adaptive control to determine the cell SOC and its electric impedance is presented. The applicability of this dual estimator is verified using measurement data acquired from a commercial LiFePO4 cell. Due to a better handling of the hysteresis problem, results show the benefits of the proposed method against the estimation with an Extended Kalman filter.

Multi-temperature state-dependent equivalent circuit discharge model for lithium-sulfur batteries

DEFF Research Database (Denmark)

Propp, Karsten; Marinescu, Monica; Auger, Daniel J.

2016-01-01

Lithium-sulfur (Li-S) batteries are described extensively in the literature, but existing computational models aimed at scientific understanding are too complex for use in applications such as battery management. Computationally simple models are vital for exploitation. This paper proposes a non......-linear state-of-charge dependent Li-S equivalent circuit network (ECN) model for a Li-S cell under discharge. Li-S batteries are fundamentally different to Li-ion batteries, and require chemistry-specific models. A new Li-S model is obtained using a ‘behavioural’ interpretation of the ECN model; as Li...... pulse profile at four temperatures from 10 °C to 50 °C, giving linearized ECN parameters for a range of states-of-charge, currents and temperatures. These are used to create a nonlinear polynomial-based battery model suitable for use in a battery management system. When the model is used to predict...

Batteries 2020 – Lithium - ion battery first and second life ageing, validated battery models, lifetime modelling and ageing assessment of thermal parameters

DEFF Research Database (Denmark)

Timmermans, Jean-Marc; Nikolian, Alexandros; De Hoog, Joris

2016-01-01

The European Project “Batteries 2020” unites nine partners jointly working on research and the development of competitive European automotive batteries. The project aims at increasing both the energy density and lifetime of large format pouch lithium-ion batteries towards the goals targeted...... vehicle application. These batteries are still operational and suitable to less restrictive conditions, such as those for stationary and renewable energy application. Therefore, possible second life opportunities have been identified and further assessed. In this paper, the main ageing effects of lithium...... ion batteries are explained. Next, an overview of different validated battery models will be discussed. Finally, a methodology for assessing the performance of the battery cells in a second life application is presented....

Technoeconomic Modeling of Battery Energy Storage in SAM

Energy Technology Data Exchange (ETDEWEB)

DiOrio, Nicholas [National Renewable Energy Lab. (NREL), Golden, CO (United States); Dobos, Aron [National Renewable Energy Lab. (NREL), Golden, CO (United States); Janzou, Steven [National Renewable Energy Lab. (NREL), Golden, CO (United States); Nelson, Austin [National Renewable Energy Lab. (NREL), Golden, CO (United States); Lundstrom, Blake [National Renewable Energy Lab. (NREL), Golden, CO (United States)

2015-09-01

Detailed comprehensive lead-acid and lithium-ion battery models have been integrated with photovoltaic models in an effort to allow System Advisor Model (SAM) to offer the ability to predict the performance and economic benefit of behind the meter storage. In a system with storage, excess PV energy can be saved until later in the day when PV production has fallen, or until times of peak demand when it is more valuable. Complex dispatch strategies can be developed to leverage storage to reduce energy consumption or power demand based on the utility rate structure. This document describes the details of the battery performance and economic models in SAM.

Estimation of power lithium-ion battery SOC based on fuzzy optimal decision

Science.gov (United States)

He, Dongmei; Hou, Enguang; Qiao, Xin; Liu, Guangmin

2018-06-01

In order to improve vehicle performance and safety, need to accurately estimate the power lithium battery state of charge (SOC), analyzing the common SOC estimation methods, according to the characteristics open circuit voltage and Kalman filter algorithm, using T - S fuzzy model, established a lithium battery SOC estimation method based on the fuzzy optimal decision. Simulation results show that the battery model accuracy can be improved.

A physics-based fractional order model and state of energy estimation for lithium ion batteries. Part II: Parameter identification and state of energy estimation for LiFePO4 battery

Science.gov (United States)

Li, Xiaoyu; Pan, Ke; Fan, Guodong; Lu, Rengui; Zhu, Chunbo; Rizzoni, Giorgio; Canova, Marcello

2017-11-01

State of energy (SOE) is an important index for the electrochemical energy storage system in electric vehicles. In this paper, a robust state of energy estimation method in combination with a physical model parameter identification method is proposed to achieve accurate battery state estimation at different operating conditions and different aging stages. A physics-based fractional order model with variable solid-state diffusivity (FOM-VSSD) is used to characterize the dynamic performance of a LiFePO4/graphite battery. In order to update the model parameter automatically at different aging stages, a multi-step model parameter identification method based on the lexicographic optimization is especially designed for the electric vehicle operating conditions. As the battery available energy changes with different applied load current profiles, the relationship between the remaining energy loss and the state of charge, the average current as well as the average squared current is modeled. The SOE with different operating conditions and different aging stages are estimated based on an adaptive fractional order extended Kalman filter (AFEKF). Validation results show that the overall SOE estimation error is within ±5%. The proposed method is suitable for the electric vehicle online applications.

Pulse Power Capability Estimation of Lithium Titanate Oxide-based Batteries

DEFF Research Database (Denmark)

Stroe, Ana-Irina; Swierczynski, Maciej Jozef; Stroe, Daniel Loan

2016-01-01

The pulse power capability (PPC) represents one of the parameters that describe the performance behavior of Lithium-ion batteries independent on the application. Consequently, extended information about the Li-ion battery PPC and its dependence on the operating conditions become necessary. Thus......, this paper analyzes the power capability characteristic of a 13Ah high power Lithium Titanate Oxide-based battery and its dependence on temperature, load current and state-of-charge. Furthermore, a model to predict the discharging PPC of the battery cell at different temperatures and load currents for three...

On electric vehicle battery charger modeling

OpenAIRE

Sainz Sapera, Luis; Mesas García, Juan José; Balcells Sendra, Josep

2011-01-01

The increase of electric vehicle (EV) battery chargers connected to electric networks could lead to future harmonic problems in power systems. These loads are nonlinear devices that inject harmonic currents and pollute network voltages. Thus, battery charger modeling must be studied in detail to determine their harmonic emissions and prevent future problems. This paper investigates EV battery charger behavior, analyzes its equivalent circuit and reports a model for each ...

An Advanced HIL Simulation Battery Model for Battery Management System Testing

DEFF Research Database (Denmark)

Barreras, Jorge Varela; Fleischer, Christian; Christensen, Andreas Elkjær

2016-01-01

Developers and manufacturers of battery management systems (BMSs) require extensive testing of controller Hardware (HW) and Software (SW), such as analog front-end and performance of generated control code. In comparison with the tests conducted on real batteries, tests conducted on a state......-of-the-art hardware-in-the-loop (HIL) simulator can be more cost and time effective, easier to reproduce, and safer beyond the normal range of operation, especially at early stages in the development process or during fault insertion. In this paper, an HIL simulation battery model is developed for purposes of BMS...... testing on a commercial HIL simulator. A multicell electrothermal Li-ion battery (LIB) model is integrated in a system-level simulation. Then, the LIB system model is converted to C code and run in real time with the HIL simulator. Finally, in order to demonstrate the capabilities of the setup...

A Lithium-Ion Battery Simulator Based on a Diffusion and Switching Overpotential Hybrid Model for Dynamic Discharging Behavior and Runtime Predictions

Directory of Open Access Journals (Sweden)

Lan-Rong Dung

2016-01-01

Full Text Available A new battery simulator based on a hybrid model is proposed in this paper for dynamic discharging behavior and runtime predictions in existing electronic simulation environments, e.g., PSIM, so it can help power circuit designers to develop and optimize their battery-powered electronic systems. The hybrid battery model combines a diffusion model and a switching overpotential model, which automatically switches overpotential resistance mode or overpotential voltage mode to accurately describe the voltage difference between battery electro-motive force (EMF and terminal voltage. Therefore, this simulator can simply run in an electronic simulation software with less computational efforts and estimate battery performances by further considering nonlinear capacity effects. A linear extrapolation technique is adopted for extracting model parameters from constant current discharging tests, so the EMF hysteresis problem is avoided. For model validation, experiments and simulations in MATLAB and PSIM environments are conducted with six different profiles, including constant loads, an interrupted load, increasing and decreasing loads and a varying load. The results confirm the usefulness and accuracy of the proposed simulator. The behavior and runtime prediction errors can be as low as 3.1% and 1.2%, respectively.

Performance Model for High-Power Lithium Titanate Oxide Batteries based on Extended Characterization Tests

DEFF Research Database (Denmark)

Stroe, Ana-Irina; Swierczynski, Maciej Jozef; Stroe, Daniel Ioan

2015-01-01

Lithium-ion (Li-ion) batteries are found nowadays not only in portable/consumer electronics but also in more power demanding applications, such as stationary renewable energy storage, automotive and back-up power supply, because of their superior characteristics in comparison to other energy...... storage technologies. Nevertheless, prior to be used in any of the aforementioned application, a Li-ion battery cell must be intensively characterized and its behavior needs to be understood. This can be realized by performing extended laboratory characterization tests and developing Li-ion battery...... performance models. Furthermore, accurate performance models are necessary in order to analyze the behavior of the battery cell under different mission profiles, by simulation; thus, avoiding time and cost demanding real life tests. This paper presents the development and the parametrization of a performance...

Small organic molecule based flow battery

Science.gov (United States)

Huskinson, Brian; Marshak, Michael; Aziz, Michael J.; Gordon, Roy G.; Betley, Theodore A.; Aspuru-Guzik, Alan; Er, Suleyman; Suh, Changwon

2018-05-08

The invention provides an electrochemical cell based on a new chemistry for a flow battery for large scale, e.g., gridscale, electrical energy storage. Electrical energy is stored chemically at an electrochemical electrode by the protonation of small organic molecules called quinones to hydroquinones. The proton is provided by a complementary electrochemical reaction at the other electrode. These reactions are reversed to deliver electrical energy. A flow battery based on this concept can operate as a closed system. The flow battery architecture has scaling advantages over solid electrode batteries for large scale energy storage.

Rapid Estimation Method for State of Charge of Lithium-Ion Battery Based on Fractional Continual Variable Order Model

Directory of Open Access Journals (Sweden)

Xin Lu

2018-03-01

Full Text Available In recent years, the fractional order model has been employed to state of charge (SOC estimation. The non integer differentiation order being expressed as a function of recursive factors defining the fractality of charge distribution on porous electrodes. The battery SOC affects the fractal dimension of charge distribution, therefore the order of the fractional order model varies with the SOC at the same condition. This paper proposes a new method to estimate the SOC. A fractional continuous variable order model is used to characterize the fractal morphology of charge distribution. The order identification results showed that there is a stable monotonic relationship between the fractional order and the SOC after the battery inner electrochemical reaction reaches balanced. This feature makes the proposed model particularly suitable for SOC estimation when the battery is in the resting state. Moreover, a fast iterative method based on the proposed model is introduced for SOC estimation. The experimental results showed that the proposed iterative method can quickly estimate the SOC by several iterations while maintaining high estimation accuracy.

Enhanced online model identification and state of charge estimation for lithium-ion battery with a FBCRLS based observer

International Nuclear Information System (INIS)

Wei, Zhongbao; Meng, Shujuan; Xiong, Binyu; Ji, Dongxu; Tseng, King Jet

2016-01-01

Highlights: • Integrated online model identification and SOC estimate is explored. • Noise variances are online estimated in a data-driven way. • Identification bias caused by noise corruption is attenuated. • SOC is online estimated with high accuracy and fast convergence. • Algorithm comparison shows the superiority of proposed method. - Abstract: State of charge (SOC) estimators with online identified battery model have proven to have high accuracy and better robustness due to the timely adaption of time varying model parameters. In this paper, we show that the common methods for model identification are intrinsically biased if both the current and voltage sensors are corrupted with noises. The uncertainties in battery model further degrade the accuracy and robustness of SOC estimate. To address this problem, this paper proposes a novel technique which integrates the Frisch scheme based bias compensating recursive least squares (FBCRLS) with a SOC observer for enhanced model identification and SOC estimate. The proposed method online estimates the noise statistics and compensates the noise effect so that the model parameters can be extracted without bias. The SOC is further estimated in real time with the online updated and unbiased battery model. Simulation and experimental studies show that the proposed FBCRLS based observer effectively attenuates the bias on model identification caused by noise contamination and as a consequence provides more reliable estimate on SOC. The proposed method is also compared with other existing methods to highlight its superiority in terms of accuracy and convergence speed.

A novel modeling methodology of open circuit voltage hysteresis for LiFePO4 batteries based on an adaptive discrete Preisach model

International Nuclear Information System (INIS)

Zhu, Letao; Sun, Zechang; Dai, Haifeng; Wei, Xuezhe

2015-01-01

Highlights: • An adaptive discrete Preisach model (ADPM) of OCV–SOC hysteresis is proposed. • The measured current is used to adjust the weight vector in the proposed ADPM. • A deformation algorithm of ADPM is developed for the accidental current errors. • The performance of ADPM under uncertainty of measured current is investigated. • The performance of ADPM under uncertainty of OCV is investigated. - Abstract: The relationship of open circuit voltage (OCV) versus state of charge (SOC) is critical for many techniques such as accurate battery modeling and reliable SOC estimation. However, the hysteresis existing in OCV–SOC curves of lithium-ion batteries complicates this relationship especially for lithium iron phosphate (LiFePO 4 ) batteries which exhibit a very flat OCV–SOC hysteretic feature. This paper aims at modeling the OCV–SOC hysteresis for LiFePO 4 batteries. The modeling approach is a novel adaptive discrete Preisach model (ADPM) based on the classic Preisach model and the least mean square (LMS) theory. To enhance the performance, the ADPM uses the measured current at each time step to adjust the weight vector. This method significantly decreases the errors (<1%) between the model predicted SOC and the true SOC acquired from experiments. A deformation algorithm of ADPM is further proposed to guarantee the performance even when large errors appear in the measured current. For further applications of the proposed ADPM such as SOC estimation, the robust performance of ADPM is also discussed when considering OCV input errors and measurement current errors. The results show that the maximum SOC calculation errors are about 6% and 5% respectively against uncertain OCV input and measured current which indicate the enormous potential of ADPM in battery management systems

Cycle life performance of rechargeable lithium ion batteries and mathematical modeling

Science.gov (United States)

Ning, Gang

Capacity fade of commercial Sony US 18650 Li-ion batteries cycled at high discharge rates was studied at ambient temperature. Battery cycled at the highest discharge rate (3 C) shows the largest internal resistance increase of 27.7% relative to the resistance of fresh battery. It's been observed anode carbon loses 10.6% of its capability to intercalate or deintercalate Li+ after it was subjected to 300 cycles at discharge rate of 3 C. This loss dominates capacity fade of full battery. A mechanism considering continuous parasitic reaction at anode/electrolyte interface and film thickening has been proposed. First principles based charge-discharge models to simulate cycle life behavior of rechargeable Li-ion batteries have been developed. In the generalized model, transport in both electrolyte phase and solid phase were simultaneously taken into account. Under mild charge-discharge condition, transport of lithium in the electrolyte phase has been neglected in the simplified model. Both models are based on loss of the active lithium ions due to the electrochemical parasitic reaction at anode/electrolyte interface and on rise of the anode film resistance. The effect of parameters such as depth of discharge (DOD), end of charge voltage (EOCV) and overvoltage of the parasitic reaction on the cycle life behavior of a battery has been analyzed. The experimental results obtained at a charge rate of 1 C, discharge rate of 0.5 C, EOCV of 4.0 V and DOD of 0.4 have been used to validate cycle life models. Good agreement between the simulations and the experiments has been achieved up to 1968 cycles with both models. Simulation of cycle life of battery under multiple cycling regimes has also been demonstrated.

Battery model for electrical power system energy balance

Science.gov (United States)

Hafen, D. P.

1983-01-01

A model to simulate nickel-cadmium battery performance and response in a spacecraft electrical power system energy balance calculation was developed. The voltage of the battery is given as a function of temperature, operating depth-of-charge (DOD), and battery state-of-charge. Also accounted for is charge inefficiency. A battery is modeled by analysis of the results of a multiparameter battery cycling test at various temperatures and DOD's.

Adaptive thermal modeling of Li-ion batteries

International Nuclear Information System (INIS)

Shadman Rad, M.; Danilov, D.L.; Baghalha, M.; Kazemeini, M.; Notten, P.H.L.

2013-01-01

Highlights: • A simple, accurate and adaptive thermal model is proposed for Li-ion batteries. • Equilibrium voltages, overpotentials and entropy changes are quantified from experimental results. • Entropy changes are highly dependent on the battery State-of-Charge. • Good agreement between simulated and measured heat development is obtained under all conditions. • Radiation contributes to about 50% of heat dissipation at elevated temperatures. -- Abstract: An accurate thermal model to predict the heat generation in rechargeable batteries is an essential tool for advanced thermal management in high power applications, such as electric vehicles. For such applications, the battery materials’ details and cell design are normally not provided. In this work a simple, though accurate, thermal model for batteries has been developed, considering the temperature- and current-dependent overpotential heat generation and State-of-Charge dependent entropy contributions. High power rechargeable Li-ion (7.5 Ah) batteries have been experimentally investigated and the results are used for model verification. It is shown that the State-of-Charge dependent entropy is a significant heat source and is therefore essential to correctly predict the thermal behavior of Li-ion batteries under a wide variety of operating conditions. An adaptive model is introduced to obtain these entropy values. A temperature-dependent equation for heat transfer to the environment is also taken into account. Good agreement between the simulations and measurements is obtained in all cases. The parameters for both the heat generation and heat transfer processes can be applied to the thermal design of advanced battery packs. The proposed methodology is generic and independent on the cell chemistry and battery design. The parameters for the adaptive model can be determined by performing simple cell potential/current and temperature measurements for a limited number of charge/discharge cycles

An Acausal Li-Ion Battery Pack Model for Automotive Applications

Directory of Open Access Journals (Sweden)

Kotub Uddin

2014-08-01

Full Text Available In this work, a novel acausal and reconfigurable battery pack model is presented. The model structure adopted for the battery cell is based on an equivalent circuit representation. The circuit elements are modified to take account of both hysteresis and diffusion limitation. The latter is known to be a nonlinear function of large operating currents or long operating times. It is shown that the integration of a current dependent time constant within the cell model better emulates the solid diffusional dynamics of lithium intercalation into the active material under large electrical loads. The advantages of an acausal modeling approach, when scaling-up individual cell models into a complete battery system are also presented. Particular consideration is given to emulating the impact of cell to cell variations on pack performance. Using statistical analysis of battery tests, cell model parameter variations are characterized and quantified. The cell and scaled-up pack model are parameterized for a number of commercially available cell formats, energy capacities and chemistries. The new models are validated using transient, real-world, electrical data measured from an electric vehicle (EV operating within an urban environment.

Adaptive Kalman filter based state of charge estimation algorithm for lithium-ion battery

International Nuclear Information System (INIS)

Zheng Hong; Liu Xu; Wei Min

2015-01-01

In order to improve the accuracy of the battery state of charge (SOC) estimation, in this paper we take a lithium-ion battery as an example to study the adaptive Kalman filter based SOC estimation algorithm. Firstly, the second-order battery system model is introduced. Meanwhile, the temperature and charge rate are introduced into the model. Then, the temperature and the charge rate are adopted to estimate the battery SOC, with the help of the parameters of an adaptive Kalman filter based estimation algorithm model. Afterwards, it is verified by the numerical simulation that in the ideal case, the accuracy of SOC estimation can be enhanced by adding two elements, namely, the temperature and charge rate. Finally, the actual road conditions are simulated with ADVISOR, and the simulation results show that the proposed method improves the accuracy of battery SOC estimation under actual road conditions. Thus, its application scope in engineering is greatly expanded. (paper)

Electronic network modeling of rechargeable batteries: II: The NiCd system

NARCIS (Netherlands)

Notten, P.H.L.; Kruijt, W.S.; Bergveld, H.J.

1998-01-01

Based on the concept of a defined sealed rechargeable NiCd battery, the mathematics of the various electrochemical and physical processes occurring inside the battery are described. Subsequently, these sets of mathematical equations are clustered and converted into an electronic network model.

Predictive Models of Li-ion Battery Lifetime (Presentation)

Energy Technology Data Exchange (ETDEWEB)

Smith, K.; Wood, E.; Santhanagopalan, S.; Kim, G.; Shi, Y.; Pesaran, A.

2014-09-01

Predictive models of Li-ion battery reliability must consider a multiplicity of electrochemical, thermal and mechanical degradation modes experienced by batteries in application environments. Complicating matters, Li-ion batteries can experience several path dependent degradation trajectories dependent on storage and cycling history of the application environment. Rates of degradation are controlled by factors such as temperature history, electrochemical operating window, and charge/discharge rate. Lacking accurate models and tests, lifetime uncertainty must be absorbed by overdesign and warranty costs. Degradation models are needed that predict lifetime more accurately and with less test data. Models should also provide engineering feedback for next generation battery designs. This presentation reviews both multi-dimensional physical models and simpler, lumped surrogate models of battery electrochemical and mechanical degradation. Models are compared with cell- and pack-level aging data from commercial Li-ion chemistries. The analysis elucidates the relative importance of electrochemical and mechanical stress-induced degradation mechanisms in real-world operating environments. Opportunities for extending the lifetime of commercial battery systems are explored.

Mesoscopic modeling and parameter estimation of a lithium-ion battery based on LiFePO4/graphite

Science.gov (United States)

Jokar, Ali; Désilets, Martin; Lacroix, Marcel; Zaghib, Karim

2018-03-01

A novel numerical model for simulating the behavior of lithium-ion batteries based on LiFePO4(LFP)/graphite is presented. The model is based on the modified Single Particle Model (SPM) coupled to a mesoscopic approach for the LFP electrode. The model comprises one representative spherical particle as the graphite electrode, and N LFP units as the positive electrode. All the SPM equations are retained to model the negative electrode performance. The mesoscopic model rests on non-equilibrium thermodynamic conditions and uses a non-monotonic open circuit potential for each unit. A parameter estimation study is also carried out to identify all the parameters needed for the model. The unknown parameters are the solid diffusion coefficient of the negative electrode (Ds,n), reaction-rate constant of the negative electrode (Kn), negative and positive electrode porosity (εn&εn), initial State-Of-Charge of the negative electrode (SOCn,0), initial partial composition of the LFP units (yk,0), minimum and maximum resistance of the LFP units (Rmin&Rmax), and solution resistance (Rcell). The results show that the mesoscopic model can simulate successfully the electrochemical behavior of lithium-ion batteries at low and high charge/discharge rates. The model also describes adequately the lithiation/delithiation of the LFP particles, however, it is computationally expensive compared to macro-based models.

Vesicle-based rechargeable batteries

Energy Technology Data Exchange (ETDEWEB)

Stanish, I.; Singh, A. [Center for Bio/Molecular Science and Engineering, Naval Research Laboratory, 4555 Overlook Ave., S.W., Washington, DC 20375 (United States); Lowy, D.A. [Nova Research, Inc., 1900 Elkin St., Alexandria, VA 22308 (United States); Hung, C.W. [Department of Chemical Engineering, University of Maryland, College Park, MD 20742 (United States)

2005-05-02

Vesicle-based rechargeable batteries can be fabricated by mounting polymerized vesicles filled with ferrocyanide or ferricyanide to a conductive surface. The potential can be adjusted by changing the concentration ratio of hydroquinone and benzoquinone bound to the vesicle membranes. These batteries show promise as a means of supplying portable power for future autonomous nanosystems. (Abstract Copyright [2005], Wiley Periodicals, Inc.)

High-Fidelity Battery Model for Model Predictive Control Implemented into a Plug-In Hybrid Electric Vehicle

Directory of Open Access Journals (Sweden)

Nicolas Sockeel

2017-04-01

Full Text Available Power management strategies have impacts on fuel economy, greenhouse gasses (GHG emission, as well as effects on the durability of power-train components. This is why different off-line and real-time optimal control approaches are being developed. However, real-time control seems to be more attractive than off-line control because it can be directly implemented for managing power and energy flows inside an actual vehicle. One interesting illustration of these power management strategies is the model predictive control (MPC based algorithm. Inside a MPC, a cost function is optimized while system constraints are validated in real time. The MPC algorithm relies on dynamic models of the vehicle and the battery. The complexity and accuracy of the battery model are usually neglected to benefit the development of new cost functions or better MPC algorithms. The contribution of this manuscript consists of developing and evaluating a high-fidelity battery model of a plug-in hybrid electric vehicle (PHEV that has been used for MPC. Via empirical work and simulation, the impact of a high-fidelity battery model has been evaluated and compared to a simpler model in the context of MPC. It is proven that the new battery model reduces the absolute voltage, state of charge (SoC, and battery power loss error by a factor of 3.2, 1.9 and 2.1 on average respectively, compared to the simpler battery model.

Electrode Nanostructures in Lithium‐Based Batteries

Science.gov (United States)

Mahmood, Nasir

2014-01-01

Lithium‐based batteries possessing energy densities much higher than those of the conventional batteries belong to the most promising class of future energy devices. However, there are some fundamental issues related to their electrodes which are big roadblocks in their applications to electric vehicles (EVs). Nanochemistry has advantageous roles to overcome these problems by defining new nanostructures of electrode materials. This review article will highlight the challenges associated with these chemistries both to bring high performance and longevity upon considering the working principles of the various types of lithium‐based (Li‐ion, Li‐air and Li‐S) batteries. Further, the review discusses the advantages and challenges of nanomaterials in nanostructured electrodes of lithium‐based batteries, concerns with lithium metal anode and the recent advancement in electrode nanostructures. PMID:27980896

New Electro-Thermal Battery Pack Model of an Electric Vehicle

Directory of Open Access Journals (Sweden)

Muhammed Alhanouti

2016-07-01

Full Text Available Since the evolution of the electric and hybrid vehicle, the analysis of batteries’ characteristics and influence on driving range has become essential. This fact advocates the necessity of accurate simulation modeling for batteries. Different models for the Li-ion battery cell are reviewed in this paper and a group of the highly dynamic models is selected for comparison. A new open circuit voltage (OCV model is proposed. The new model can simulate the OCV curves of lithium iron magnesium phosphate (LiFeMgPO4 battery type at different temperatures. It also considers both charging and discharging cases. The most remarkable features from different models, in addition to the proposed OCV model, are integrated in a single hybrid electrical model. A lumped thermal model is implemented to simulate the temperature development in the battery cell. The synthesized electro-thermal battery cell model is extended to model a battery pack of an actual electric vehicle. Experimental tests on the battery, as well as drive tests on the vehicle are performed. The proposed model demonstrates a higher modeling accuracy, for the battery pack voltage, than the constituent models under extreme maneuver drive tests.

Fuzzy logic modeling of EIS measurements on lithium-ion batteries

International Nuclear Information System (INIS)

Singh, Pritpal; Vinjamuri, Ramana; Wang, Xiquan; Reisner, David

2006-01-01

A fuzzy logic-based state of health (SOH) meter is being developed for lithium-ion (Li-ion) batteries for potential use in portable defibrillators. Electrochemical impedance spectroscopy (EIS) measurements have been made from which input parameters for a fuzzy logic model to estimate the state of charge (SOC) and SOH are derived. The batteries are discharged continuously at a 1.4 A load current to simulate the constant current draw during the monitoring and recording of a patient's EKG, and periodically interrupted by 10 A pulses to simulate the battery discharge to charge up the capacitor that is in turn discharged to supply high voltage to the electrodes for the defibrillation of the patient. The test procedures included both voltage recovery and EIS measurements, and were made as the batteries were being discharged and over 30 charge/discharge cycles. Accurate models have been developed to estimate the number of pulses that the battery pack can deliver at various stages of its cycle life (SOC measure) and the number of charge/discharge cycles (SOH measure) that it had undergone

A numerical model for a thermally-regenerative ammonia-based flow battery using for low grade waste heat recovery

Science.gov (United States)

Wang, Weiguang; Shu, Gequn; Tian, Hua; Zhu, Xiuping

2018-06-01

A stationary and a transient two-dimensional models, based on the universal conservation laws and coupled with electrochemical reactions, are firstly applied to describe a single thermally-regenerative ammonia-based flow battery (TR-AFB), and emphasis is placed on studying the effects of reactant concentrations, physical properties of the electrolyte, flow rates and geometric parameters of flow channels on the battery performance. The model includes several experimental parameters measured by cyclic voltammetry (CV), chronoamperometry (CA) and Tafel plot. The results indicate that increasing NH3 concentration has a decisive effect on the improvement of power production and is beneficial to use higher Cu2+ concentrations, but the endurance of membrane and self-discharge need to be considered at the same time. It is also suggested that appropriately reducing the initial Cu(NH3)42+ concentration can promote power and energy densities and mitigate cyclical fluctuation. The relation between the energy and power densities is given, and the models are validated by some experimental data.

Residual lifetime prediction for lithium-ion battery based on functional principal component analysis and Bayesian approach

International Nuclear Information System (INIS)

Cheng, Yujie; Lu, Chen; Li, Tieying; Tao, Laifa

2015-01-01

Existing methods for predicting lithium-ion (Li-ion) battery residual lifetime mostly depend on a priori knowledge on aging mechanism, the use of chemical or physical formulation and analytical battery models. This dependence is usually difficult to determine in practice, which restricts the application of these methods. In this study, we propose a new prediction method for Li-ion battery residual lifetime evaluation based on FPCA (functional principal component analysis) and Bayesian approach. The proposed method utilizes FPCA to construct a nonparametric degradation model for Li-ion battery, based on which the residual lifetime and the corresponding confidence interval can be evaluated. Furthermore, an empirical Bayes approach is utilized to achieve real-time updating of the degradation model and concurrently determine residual lifetime distribution. Based on Bayesian updating, a more accurate prediction result and a more precise confidence interval are obtained. Experiments are implemented based on data provided by the NASA Ames Prognostics Center of Excellence. Results confirm that the proposed prediction method performs well in real-time battery residual lifetime prediction. - Highlights: • Capacity is considered functional and FPCA is utilized to extract more information. • No features required which avoids drawbacks induced by feature extraction. • A good combination of both population and individual information. • Avoiding complex aging mechanism and accurate analytical models of batteries. • Easily applicable to different batteries for life prediction and RLD calculation.

Comparisons of Modeling and State of Charge Estimation for Lithium-Ion Battery Based on Fractional Order and Integral Order Methods

Directory of Open Access Journals (Sweden)

Renxin Xiao

2016-03-01

Full Text Available In order to properly manage lithium-ion batteries of electric vehicles (EVs, it is essential to build the battery model and estimate the state of charge (SOC. In this paper, the fractional order forms of Thevenin and partnership for a new generation of vehicles (PNGV models are built, of which the model parameters including the fractional orders and the corresponding resistance and capacitance values are simultaneously identified based on genetic algorithm (GA. The relationships between different model parameters and SOC are established and analyzed. The calculation precisions of the fractional order model (FOM and integral order model (IOM are validated and compared under hybrid test cycles. Finally, extended Kalman filter (EKF is employed to estimate the SOC based on different models. The results prove that the FOMs can simulate the output voltage more accurately and the fractional order EKF (FOEKF can estimate the SOC more precisely under dynamic conditions.

Impedance Characterization and Modeling of Lithium-Ion Batteries Considering the Internal Temperature Gradient

Directory of Open Access Journals (Sweden)

Haifeng Dai

2018-01-01

Full Text Available Battery impedance is essential to the management of lithium-ion batteries for electric vehicles (EVs, and impedance characterization can help to monitor and predict the battery states. Many studies have been undertaken to investigate impedance characterization and the factors that influence impedance. However, few studies regarding the influence of the internal temperature gradient, which is caused by heat generation during operation, have been presented. We have comprehensively studied the influence of the internal temperature gradient on impedance characterization and the modeling of battery impedance, and have proposed a discretization model to capture battery impedance characterization considering the temperature gradient. Several experiments, including experiments with artificial temperature gradients, are designed and implemented to study the influence of the internal temperature gradient on battery impedance. Based on the experimental results, the parameters of the non-linear impedance model are obtained, and the relationship between the parameters and temperature is further established. The experimental results show that the temperature gradient will influence battery impedance and the temperature distribution can be considered to be approximately linear. The verification results indicate that the proposed discretization model has a good performance and can be used to describe the actual characterization of the battery with an internal temperature gradient.

Numerical modeling of an all vanadium redox flow battery.

Energy Technology Data Exchange (ETDEWEB)

Clausen, Jonathan R.; Brunini, Victor E.; Moffat, Harry K.; Martinez, Mario J.

2014-01-01

We develop a capability to simulate reduction-oxidation (redox) flow batteries in the Sierra Multi-Mechanics code base. Specifically, we focus on all-vanadium redox flow batteries; however, the capability is general in implementation and could be adopted to other chemistries. The electrochemical and porous flow models follow those developed in the recent publication by [28]. We review the model implemented in this work and its assumptions, and we show several verification cases including a binary electrolyte, and a battery half-cell. Then, we compare our model implementation with the experimental results shown in [28], with good agreement seen. Next, a sensitivity study is conducted for the major model parameters, which is beneficial in targeting specific features of the redox flow cell for improvement. Lastly, we simulate a three-dimensional version of the flow cell to determine the impact of plenum channels on the performance of the cell. Such channels are frequently seen in experimental designs where the current collector plates are borrowed from fuel cell designs. These designs use a serpentine channel etched into a solid collector plate.

Modelling Thermal Effects of Battery Cells inside Electric Vehicle Battery Packs

DEFF Research Database (Denmark)

Khan, Mohammad Rezwan; Kær, Søren Knudsen

The poster presents a methodology to account for thermal effects on battery cells to improve the typical thermal performances in a pack through heating calculations generally performed under the operating condition assumption. The aim is to analyze the issues based on battery thermo-physical char...

Modeling the Lithium Ion Battery

Science.gov (United States)

Summerfield, John

2013-01-01

The lithium ion battery will be a reliable electrical resource for many years to come. A simple model of the lithium ions motion due to changes in concentration and voltage is presented. The battery chosen has LiCoO[subscript 2] as the cathode, LiPF[subscript 6] as the electrolyte, and LiC[subscript 6] as the anode. The concentration gradient and…

An improved theoretical electrochemical-thermal modelling of lithium-ion battery packs in electric vehicles

Science.gov (United States)

Amiribavandpour, Parisa; Shen, Weixiang; Mu, Daobin; Kapoor, Ajay

2015-06-01

A theoretical electrochemical thermal model combined with a thermal resistive network is proposed to investigate thermal behaviours of a battery pack. The combined model is used to study heat generation and heat dissipation as well as their influences on the temperatures of the battery pack with and without a fan under constant current discharge and variable current discharge based on electric vehicle (EV) driving cycles. The comparison results indicate that the proposed model improves the accuracy in the temperature predication of the battery pack by 2.6 times. Furthermore, a large battery pack with four of the investigated battery packs in series is simulated in the presence of different ambient temperatures. The simulation results show that the temperature of the large battery pack at the end of EV driving cycles can reach to 50 °C or 60 °C in high ambient temperatures. Therefore, thermal management system in EVs is required to maintain the battery pack within the safe temperature range.

Enhanced battery model including temperature effects

NARCIS (Netherlands)

Rosca, B.; Wilkins, S.

2013-01-01

Within electric and hybrid vehicles, batteries are used to provide/buffer the energy required for driving. However, battery performance varies throughout the temperature range specific to automotive applications, and as such, models that describe this behaviour are required. This paper presents a

Model Predictive Control for Distributed Microgrid Battery Energy Storage Systems

DEFF Research Database (Denmark)

Morstyn, Thomas; Hredzak, Branislav; Aguilera, Ricardo P.

2018-01-01

, and converter current constraints to be addressed. In addition, nonlinear variations in the charge and discharge efficiencies of lithium ion batteries are analyzed and included in the control strategy. Real-time digital simulations were carried out for an islanded microgrid based on the IEEE 13 bus prototypical......This brief proposes a new convex model predictive control (MPC) strategy for dynamic optimal power flow between battery energy storage (ES) systems distributed in an ac microgrid. The proposed control strategy uses a new problem formulation, based on a linear $d$ – $q$ reference frame voltage...... feeder, with distributed battery ES systems and intermittent photovoltaic generation. It is shown that the proposed control strategy approaches the performance of a strategy based on nonconvex optimization, while reducing the required computation time by a factor of 1000, making it suitable for a real...

Improving optimal control of grid-connected lithium-ion batteries through more accurate battery and degradation modelling

Science.gov (United States)

Reniers, Jorn M.; Mulder, Grietus; Ober-Blöbaum, Sina; Howey, David A.

2018-03-01

The increased deployment of intermittent renewable energy generators opens up opportunities for grid-connected energy storage. Batteries offer significant flexibility but are relatively expensive at present. Battery lifetime is a key factor in the business case, and it depends on usage, but most techno-economic analyses do not account for this. For the first time, this paper quantifies the annual benefits of grid-connected batteries including realistic physical dynamics and nonlinear electrochemical degradation. Three lithium-ion battery models of increasing realism are formulated, and the predicted degradation of each is compared with a large-scale experimental degradation data set (Mat4Bat). A respective improvement in RMS capacity prediction error from 11% to 5% is found by increasing the model accuracy. The three models are then used within an optimal control algorithm to perform price arbitrage over one year, including degradation. Results show that the revenue can be increased substantially while degradation can be reduced by using more realistic models. The estimated best case profit using a sophisticated model is a 175% improvement compared with the simplest model. This illustrates that using a simplistic battery model in a techno-economic assessment of grid-connected batteries might substantially underestimate the business case and lead to erroneous conclusions.

Cooling Simulation and Thermal Abuse Modeling of Lithium-Ion Batteries Using the Newman, Tiedemann, Gu, and Kim (NTGK) Model

DEFF Research Database (Denmark)

Saeed Madani, Seyed; Swierczynski, Maciej Jozef; Kær, Søren Knudsen

2017-01-01

This paper gives insight into the cooling simulation and thermal abuse modeling of lithium-ion batteries by ANSYS FLUENT. Cooling strategies are important issues in the thermal management of lithium-ion battery systems, and it is essential to investigate them attentively in order to maintain...... the functioning temperature of batteries within an optimum range. The high temperature is able not only to decrease the efficiency of batteries but also may lead to the thermal runaway. To comprehend further, the thermal abuse behavior of lithium-ion batteries based on The Newman, Tiedemann, Gu, and Kim (NTGK......) model has been implemented in ANSYS FLUENT software. The results show that to achieve an optimum energy consumption for battery cooling, a minimum value of average heat transfer coefficient can be selected in order to keep the functioning temperature of batteries within an optimum range....

Effect of battery longevity on costs and health outcomes associated with cardiac implantable electronic devices: a Markov model-based Monte Carlo simulation.

Science.gov (United States)

Schmier, Jordana K; Lau, Edmund C; Patel, Jasmine D; Klenk, Juergen A; Greenspon, Arnold J

2017-11-01

The effects of device and patient characteristics on health and economic outcomes in patients with cardiac implantable electronic devices (CIEDs) are unclear. Modeling can estimate costs and outcomes for patients with CIEDs under a variety of scenarios, varying battery longevity, comorbidities, and care settings. The objective of this analysis was to compare changes in patient outcomes and payer costs attributable to increases in battery life of implantable cardiac defibrillators (ICDs) and cardiac resynchronization therapy defibrillators (CRT-D). We developed a Monte Carlo Markov model simulation to follow patients through primary implant, postoperative maintenance, generator replacement, and revision states. Patients were simulated in 3-month increments for 15 years or until death. Key variables included Charlson Comorbidity Index, CIED type, legacy versus extended battery longevity, mortality rates (procedure and all-cause), infection and non-infectious complication rates, and care settings. Costs included procedure-related (facility and professional), maintenance, and infections and non-infectious complications, all derived from Medicare data (2004-2014, 5% sample). Outcomes included counts of battery replacements, revisions, infections and non-infectious complications, and discounted (3%) costs and life years. An increase in battery longevity in ICDs yielded reductions in numbers of revisions (by 23%), battery changes (by 44%), infections (by 23%), non-infectious complications (by 10%), and total costs per patient (by 9%). Analogous reductions for CRT-Ds were 23% (revisions), 32% (battery changes), 22% (infections), 8% (complications), and 10% (costs). Based on modeling results, as battery longevity increases, patients experience fewer adverse outcomes and healthcare costs are reduced. Understanding the magnitude of the cost benefit of extended battery life can inform budgeting and planning decisions by healthcare providers and insurers.

A novel multi-model probability battery state of charge estimation approach for electric vehicles using H-infinity algorithm

International Nuclear Information System (INIS)

Lin, Cheng; Mu, Hao; Xiong, Rui; Shen, Weixiang

2016-01-01

Highlights: • A novel multi-model probability battery SOC fusion estimation approach was proposed. • The linear matrix inequality-based H∞ technique is employed to estimate the SOC. • The Bayes theorem has been employed to realize the optimal weight for the fusion. • The robustness of the proposed approach is verified by different batteries. • The results show that the proposed method can promote global estimation accuracy. - Abstract: Due to the strong nonlinearity and complex time-variant property of batteries, the existing state of charge (SOC) estimation approaches based on a single equivalent circuit model (ECM) cannot provide the accurate SOC for the entire discharging period. This paper aims to present a novel SOC estimation approach based on a multiple ECMs fusion method for improving the practical application performance. In the proposed approach, three battery ECMs, namely the Thevenin model, the double polarization model and the 3rd order RC model, are selected to describe the dynamic voltage of lithium-ion batteries and the genetic algorithm is then used to determine the model parameters. The linear matrix inequality-based H-infinity technique is employed to estimate the SOC from the three models and the Bayes theorem-based probability method is employed to determine the optimal weights for synthesizing the SOCs estimated from the three models. Two types of lithium-ion batteries are used to verify the feasibility and robustness of the proposed approach. The results indicate that the proposed approach can improve the accuracy and reliability of the SOC estimation against uncertain battery materials and inaccurate initial states.

A Real-Time Joint Estimator for Model Parameters and State of Charge of Lithium-Ion Batteries in Electric Vehicles

Directory of Open Access Journals (Sweden)

Jianping Gao

2015-08-01

Full Text Available Accurate state of charge (SoC estimation of batteries plays an important role in promoting the commercialization of electric vehicles. The main work to be done in accurately determining battery SoC can be summarized in three parts. (1 In view of the model-based SoC estimation flow diagram, the n-order resistance-capacitance (RC battery model is proposed and expected to accurately simulate the battery’s major time-variable, nonlinear characteristics. Then, the mathematical equations for model parameter identification and SoC estimation of this model are constructed. (2 The Akaike information criterion is used to determine an optimal tradeoff between battery model complexity and prediction precision for the n-order RC battery model. Results from a comparative analysis show that the first-order RC battery model is thought to be the best based on the Akaike information criterion (AIC values. (3 The real-time joint estimator for the model parameter and SoC is constructed, and the application based on two battery types indicates that the proposed SoC estimator is a closed-loop identification system where the model parameter identification and SoC estimation are corrected mutually, adaptively and simultaneously according to the observer values. The maximum SoC estimation error is less than 1% for both battery types, even against the inaccurate initial SoC.

On-line adaptive battery impedance parameter and state estimation considering physical principles in reduced order equivalent circuit battery models. Part 1. Requirements, critical review of methods and modeling

Science.gov (United States)

Fleischer, Christian; Waag, Wladislaw; Heyn, Hans-Martin; Sauer, Dirk Uwe

2014-08-01

Lithium-ion battery systems employed in high power demanding systems such as electric vehicles require a sophisticated monitoring system to ensure safe and reliable operation. Three major states of the battery are of special interest and need to be constantly monitored, these include: battery state of charge (SoC), battery state of health (capcity fade determination, SoH), and state of function (power fade determination, SoF). In a series of two papers, we propose a system of algorithms based on a weighted recursive least quadratic squares parameter estimator, that is able to determine the battery impedance and diffusion parameters for accurate state estimation. The functionality was proven on different battery chemistries with different aging conditions. The first paper investigates the general requirements on BMS for HEV/EV applications. In parallel, the commonly used methods for battery monitoring are reviewed to elaborate their strength and weaknesses in terms of the identified requirements for on-line applications. Special emphasis will be placed on real-time capability and memory optimized code for cost-sensitive industrial or automotive applications in which low-cost microcontrollers must be used. Therefore, a battery model is presented which includes the influence of the Butler-Volmer kinetics on the charge-transfer process. Lastly, the mass transport process inside the battery is modeled in a novel state-space representation.

Practical Methods in Li-ion Batteries

DEFF Research Database (Denmark)

Barreras, Jorge Varela

This thesis presents, as a collection of papers, practical methods in Li-ion batteries for simplified modeling (Manuscript I and II), battery electric vehicle design (III), battery management system testing (IV and V) and balancing system control (VI and VII). • Manuscript I tackles methodologies...... to parameterize battery models based solely on manufacturer’s datasheets • Manuscript II presents a parameterization method for battery models based on the notion of direct current resistance • Manuscript III proposes a battery electric vehicle design that combines fixed and swappable packs • Manuscript IV...... develops a battery system model for battery management system testing on a hardware-in-the-loop simulator • Manuscript V extends the previous work, introducing theoretical principles and presenting a practical method to develop ad hoc software and strategies for testing • Manuscript VI presents...

Lithium-Ion Battery Power Degradation Modelling by Electrochemical Impedance Spectroscopy

DEFF Research Database (Denmark)

Stroe, Daniel-Ioan; Swierczynski, Maciej Jozef; Stroe, Ana-Irina

2017-01-01

This paper investigates the use of the electrochemical impedance spectroscopy (EIS) technique as an alternative to the DC pulses technique for estimating the power capability decrease of Lithium-ion batteries during calendar ageing. Based on results obtained from calendar ageing tests performed...... at different conditions during one to two years, a generalized model that estimates the battery power capability decrease as function of the resistance Rs increase (obtained from EIS) was proposed and successfully verified....

State of charge estimation for lithium-ion pouch batteries based on stress measurement

International Nuclear Information System (INIS)

Dai, Haifeng; Yu, Chenchen; Wei, Xuezhe; Sun, Zechang

2017-01-01

State of charge (SOC) estimation is one of the important tasks of battery management system (BMS). Being different from other researches, a novel method of SOC estimation for pouch lithium-ion battery cells based on stress measurement is proposed. With a comprehensive experimental study, we find that, the stress of the battery during charge/discharge is composed of the static stress and the dynamic stress. The static stress, which is the measured stress in equilibrium state, corresponds to SOC, this phenomenon facilitates the design of our stress-based SOC estimation. The dynamic stress, on the other hand, is influenced by multiple factors including charge accumulation or depletion, current and historical operation, thus a multiple regression model of the dynamic stress is established. Based on the relationship between static stress and SOC, as well as the dynamic stress modeling, the SOC estimation method is founded. Experimental results show that the stress-based method performs well with a good accuracy, and this method offers a novel perspective for SOC estimation. - Highlights: • A State of Charge estimator based on stress measurement is proposed. • The stress during charge and discharge is investigated with comprehensive experiments. • Effects of SOC, current, and operation history on battery stress are well studied. • A multiple regression model of the dynamic stress is established.

Modeling Stationary Lithium-Ion Batteries for Optimization and Predictive Control: Preprint

Energy Technology Data Exchange (ETDEWEB)

Raszmann, Emma; Baker, Kyri; Shi, Ying; Christensen, Dane

2017-02-22

Accurately modeling stationary battery storage behavior is crucial to understand and predict its limitations in demand-side management scenarios. In this paper, a lithium-ion battery model was derived to estimate lifetime and state-of-charge for building-integrated use cases. The proposed battery model aims to balance speed and accuracy when modeling battery behavior for real-time predictive control and optimization. In order to achieve these goals, a mixed modeling approach was taken, which incorporates regression fits to experimental data and an equivalent circuit to model battery behavior. A comparison of the proposed battery model output to actual data from the manufacturer validates the modeling approach taken in the paper. Additionally, a dynamic test case demonstrates the effects of using regression models to represent internal resistance and capacity fading.

Computational models of an inductive power transfer system for electric vehicle battery charge

Science.gov (United States)

Anele, A. O.; Hamam, Y.; Chassagne, L.; Linares, J.; Alayli, Y.; Djouani, K.

2015-09-01

One of the issues to be solved for electric vehicles (EVs) to become a success is the technical solution of its charging system. In this paper, computational models of an inductive power transfer (IPT) system for EV battery charge are presented. Based on the fundamental principles behind IPT systems, 3 kW single phase and 22 kW three phase IPT systems for Renault ZOE are designed in MATLAB/Simulink. The results obtained based on the technical specifications of the lithium-ion battery and charger type of Renault ZOE show that the models are able to provide the total voltage required by the battery. Also, considering the charging time for each IPT model, they are capable of delivering the electricity needed to power the ZOE. In conclusion, this study shows that the designed computational IPT models may be employed as a support structure needed to effectively power any viable EV.

Computational models of an inductive power transfer system for electric vehicle battery charge

International Nuclear Information System (INIS)

Anele, A O; Hamam, Y; Djouani, K; Chassagne, L; Alayli, Y; Linares, J

2015-01-01

One of the issues to be solved for electric vehicles (EVs) to become a success is the technical solution of its charging system. In this paper, computational models of an inductive power transfer (IPT) system for EV battery charge are presented. Based on the fundamental principles behind IPT systems, 3 kW single phase and 22 kW three phase IPT systems for Renault ZOE are designed in MATLAB/Simulink. The results obtained based on the technical specifications of the lithium-ion battery and charger type of Renault ZOE show that the models are able to provide the total voltage required by the battery. Also, considering the charging time for each IPT model, they are capable of delivering the electricity needed to power the ZOE. In conclusion, this study shows that the designed computational IPT models may be employed as a support structure needed to effectively power any viable EV. (paper)

Power capability evaluation for lithium iron phosphate batteries based on multi-parameter constraints estimation

Science.gov (United States)

Wang, Yujie; Pan, Rui; Liu, Chang; Chen, Zonghai; Ling, Qiang

2018-01-01

The battery power capability is intimately correlated with the climbing, braking and accelerating performance of the electric vehicles. Accurate power capability prediction can not only guarantee the safety but also regulate driving behavior and optimize battery energy usage. However, the nonlinearity of the battery model is very complex especially for the lithium iron phosphate batteries. Besides, the hysteresis loop in the open-circuit voltage curve is easy to cause large error in model prediction. In this work, a multi-parameter constraints dynamic estimation method is proposed to predict the battery continuous period power capability. A high-fidelity battery model which considers the battery polarization and hysteresis phenomenon is presented to approximate the high nonlinearity of the lithium iron phosphate battery. Explicit analyses of power capability with multiple constraints are elaborated, specifically the state-of-energy is considered in power capability assessment. Furthermore, to solve the problem of nonlinear system state estimation, and suppress noise interference, the UKF based state observer is employed for power capability prediction. The performance of the proposed methodology is demonstrated by experiments under different dynamic characterization schedules. The charge and discharge power capabilities of the lithium iron phosphate batteries are quantitatively assessed under different time scales and temperatures.

The discharge behavior of lithium-ion batteries using the Dual-Potential Multi-Scale Multi-Dimensional (MSMD) Battery Model

DEFF Research Database (Denmark)

Saeed Madani, Seyed; Swierczynski, Maciej Jozef; Kær, Søren Knudsen

2017-01-01

This paper gives insight into the discharge behavior of lithium-ion batteries based on the investigations, which have been done by the researchers [1– 19]. In this article, the battery's discharge behaviour at various discharge rates is studied and surface monitor, discharge curve, volume monitor...... to analysis the discharge behaviour of lithium-ion batteries. The results show that surface monitor plot of discharge curve at 1 C has a decreasing trend and volume monitor plot of maximum temperature in the domain has slightly increasing pattern over the simulation time. For the curves of discharge...... plot of maximum temperature in the domain and maximum temperature in the area are illustrated. Additionally, an external and internal short-circuit treatment for three cases have been studied. The Dual-Potential Multi-Scale Multi-Dimensional (MSMD) Battery Model (BM) was used by ANSYS FLUENT software...

A Practical Circuit-based Model for State of Health Estimation of Li-ion Battery Cells in Electric Vehicles

Energy Technology Data Exchange (ETDEWEB)

Lam, Long

2011-08-23

In this thesis the development of the state of health of Li-ion battery cells under possible real-life operating conditions in electric cars has been characterised. Furthermore, a practical circuit-based model for Li-ion cells has been developed that is capable of modelling the cell voltage behaviour under various operating conditions. The Li-ion cell model can be implemented in simulation programs and be directly connected to a model of the rest of the electronic system in electric vehicles. Most existing battery models are impractical for electric vehicle system designers and require extensive background knowledge of electrochemistry to be implemented. Furthermore, many models do not take the effect of regenerative braking into account and are obtained from testing fully charged cells. However, in real-life applications electric vehicles are not always fully charged and utilise regenerative braking to save energy. To obtain a practical circuit model based on real operating conditions and to model the state of health of electric vehicle cells, numerous 18650 size LiFePO4 cells have been tested under possible operating conditions. Capacity fading was chosen as the state of health parameter, and the capacity fading of different cells was compared with the charge processed instead of cycles. Tests have shown that the capacity fading rate is dependent on temperature, charging C-rate, state of charge and depth of discharge. The obtained circuit model is capable of simulating the voltage behaviour under various temperatures and C-rates with a maximum error of 14mV. However, modelling the effect of different temperatures and C-rates increases the complexity of the model. The model is easily adjustable and the choice is given to the electric vehicle system designer to decide which operating conditions to take into account. By combining the test results for the capacity fading and the proposed circuit model, recommendations to optimise the battery lifetime are proposed.

A novel BEV concept based on fixed and swappable li-ion battery packs

DEFF Research Database (Denmark)

Barreras, Jorge Varela; Pinto, C.; de Castro, R.

2015-01-01

-based ownership models to distribute the cost of the large battery pack over the vehicle lifetime. A methodology is proposed for the analysis and evaluation of the proposed concept in comparison with a direct owned non swappable single pack BEV, proving that significant improvements on city fuel economy (up to 20......In this paper a novel battery electric vehicle (BEV) concept based on a small fixed and a big swappable li-ion battery pack is proposed in order to achieve: longer range, lower initial purchase price and lower energy consumption at short ranges. For short ranges the BEV is only powered...... by the relatively small fixed battery pack, without the large swappable battery pack. In this way the mass of the vehicle is reduced and therefore the energy consumed per unit distance is improved. For higher ranges the BEV is powered by both battery packs. This concept allows the introduction of subscription...

First principles nickel-cadmium and nickel hydrogen spacecraft battery models

Energy Technology Data Exchange (ETDEWEB)

Timmerman, P.; Ratnakumar, B.V.; Distefano, S.

1996-02-01

The principles of Nickel-Cadmium and Nickel-Hydrogen spacecraft battery models are discussed. The Ni-Cd battery model includes two phase positive electrode and its predictions are very close to actual data. But the Ni-H2 battery model predictions (without the two phase positive electrode) are unacceptable even though the model is operational. Both models run on UNIX and Macintosh computers.

A reduced low-temperature electro-thermal coupled model for lithium-ion batteries

International Nuclear Information System (INIS)

Jiang, Jiuchun; Ruan, Haijun; Sun, Bingxiang; Zhang, Weige; Gao, Wenzhong; Wang, Le Yi; Zhang, Linjing

2016-01-01

Highlights: • A reduced low-temperature electro-thermal coupled model is proposed. • A novel frequency-dependent equation for polarization parameters is presented. • The model is validated under different frequency and low-temperature conditions. • The reduced model exhibits a high accuracy with a low computational effort. • The adaptability of the proposed methodology for model reduction is verified. - Abstract: A low-temperature electro-thermal coupled model, which is based on the electrochemical mechanism, is developed to accurately capture both electrical and thermal behaviors of batteries. Activation energies reveal that temperature dependence of resistances is greater than that of capacitances. The influence of frequency on polarization voltage and irreversible heat is discussed, and frequency dependence of polarization resistance and capacitance is obtained. Based on the frequency-dependent equation, a reduced low-temperature electro-thermal coupled model is proposed and experimentally validated under different temperature, frequency and amplitude conditions. Simulation results exhibit good agreement with experimental data, where the maximum relative voltage error and temperature error are below 2.65% and 1.79 °C, respectively. The reduced model is demonstrated to have almost the same accuracy as the original model and require a lower computational effort. The effectiveness and adaptability of the proposed methodology for model reduction is verified using batteries with three different cathode materials from different manufacturers. The reduced model, thanks to its high accuracy and simplicity, provides a promising candidate for development of rapid internal heating and optimal charging strategies at low temperature, and for evaluation of the state of battery health in on-board battery management system.

Integration of sampling based battery state of health estimation method in electric vehicles

International Nuclear Information System (INIS)

Ozkurt, Celil; Camci, Fatih; Atamuradov, Vepa; Odorry, Christopher

2016-01-01

Highlights: • Presentation of a prototype system with full charge discharge cycling capability. • Presentation of SoH estimation results for systems degraded in the lab. • Discussion of integration alternatives of the presented method in EVs. • Simulation model based on presented SoH estimation for a real EV battery system. • Optimization of number of battery cells to be selected for SoH test. - Abstract: Battery cost is one of the crucial parameters affecting high deployment of Electric Vehicles (EVs) negatively. Accurate State of Health (SoH) estimation plays an important role in reducing the total ownership cost, availability, and safety of the battery avoiding early disposal of the batteries and decreasing unexpected failures. A circuit design for SoH estimation in a battery system that bases on selected battery cells and its integration to EVs are presented in this paper. A prototype microcontroller has been developed and used for accelerated aging tests for a battery system. The data collected in the lab tests have been utilized to simulate a real EV battery system. Results of accelerated aging tests and simulation have been presented in the paper. The paper also discusses identification of the best number of battery cells to be selected for SoH estimation test. In addition, different application options of the presented approach for EV batteries have been discussed in the paper.

Coupled electrochemical thermal modelling of a novel Li-ion battery pack thermal management system

International Nuclear Information System (INIS)

Basu, Suman; Hariharan, Krishnan S.; Kolake, Subramanya Mayya; Song, Taewon; Sohn, Dong Kee; Yeo, Taejung

2016-01-01

Highlights: • Three-dimensional electrochemical thermal model of Li-ion battery pack using computational fluid dynamics (CFD). • Novel pack design for compact liquid cooling based thermal management system. • Simple temperature estimation algorithm for the cells in the pack using the results from the model. • Sensitivity of the thermal performance to contact resistance has been investigated. - Abstract: Thermal management system is of critical importance for a Li-ion battery pack, as high performance and long battery pack life can be simultaneously achieved when operated within a narrow range of temperature around the room temperature. An efficient thermal management system is required to keep the battery temperature in this range, despite widely varying operating conditions. A novel liquid coolant based thermal management system, for 18,650 battery pack has been introduced herein. This system is designed to be compact and economical without compromising safety. A coupled three-dimensional (3D) electrochemical thermal model is constructed for the proposed Li-ion battery pack. The model is used to evaluate the effects of different operating conditions like coolant flow-rate and discharge current on the pack temperature. Contact resistance is found to have the strongest impact on the thermal performance of the pack. From the numerical solution, a simple and novel temperature correlation of predicting the temperatures of all the individual cells given the temperature measurement of one cell is devised and validated with experimental results. Such coefficients have great potential of reducing the sensor requirement and complexity in a large Li-ion battery pack, typical of an electric vehicle.

Lifetime modelling of lead acid batteries

DEFF Research Database (Denmark)

Bindner, H.; Cronin, T.; Lundsager, P.

2005-01-01

The performance and lifetime of energy storage in batteries are an important part of many renewable based energy systems. Not only do batteries impact on the system performance but they are also a significant expenditure when considering the whole lifecycle costs. Poor prediction of lifetime can......, therefore, lead to uncertainty in the viability of the system in the long term. This report details the work undertaken to investigate and develop two different battery life prediction methodologies withspecific reference to their use in hybrid renewable energy systems. Alongside this, results from battery...... tests designed to exercise batteries in similar modes to those that they experience in hybrid systems have also been analysed. These have yieldedbattery specific parameters for use in the prediction software and the first results in the validation process of the software are also given. This work has...

A lithium-oxygen battery based on lithium superoxide.

Science.gov (United States)

Lu, Jun; Lee, Yun Jung; Luo, Xiangyi; Lau, Kah Chun; Asadi, Mohammad; Wang, Hsien-Hau; Brombosz, Scott; Wen, Jianguo; Zhai, Dengyun; Chen, Zonghai; Miller, Dean J; Jeong, Yo Sub; Park, Jin-Bum; Fang, Zhigang Zak; Kumar, Bijandra; Salehi-Khojin, Amin; Sun, Yang-Kook; Curtiss, Larry A; Amine, Khalil

2016-01-21

Batteries based on sodium superoxide and on potassium superoxide have recently been reported. However, there have been no reports of a battery based on lithium superoxide (LiO2), despite much research into the lithium-oxygen (Li-O2) battery because of its potential high energy density. Several studies of Li-O2 batteries have found evidence of LiO2 being formed as one component of the discharge product along with lithium peroxide (Li2O2). In addition, theoretical calculations have indicated that some forms of LiO2 may have a long lifetime. These studies also suggest that it might be possible to form LiO2 alone for use in a battery. However, solid LiO2 has been difficult to synthesize in pure form because it is thermodynamically unstable with respect to disproportionation, giving Li2O2 (refs 19, 20). Here we show that crystalline LiO2 can be stabilized in a Li-O2 battery by using a suitable graphene-based cathode. Various characterization techniques reveal no evidence for the presence of Li2O2. A novel templating growth mechanism involving the use of iridium nanoparticles on the cathode surface may be responsible for the growth of crystalline LiO2. Our results demonstrate that the LiO2 formed in the Li-O2 battery is stable enough for the battery to be repeatedly charged and discharged with a very low charge potential (about 3.2 volts). We anticipate that this discovery will lead to methods of synthesizing and stabilizing LiO2, which could open the way to high-energy-density batteries based on LiO2 as well as to other possible uses of this compound, such as oxygen storage.

Prediction Model of Battery State of Charge and Control Parameter Optimization for Electric Vehicle

Directory of Open Access Journals (Sweden)

Bambang Wahono

2015-07-01

Full Text Available This paper presents the construction of a battery state of charge (SOC prediction model and the optimization method of the said model to appropriately control the number of parameters in compliance with the SOC as the battery output objectives. Research Centre for Electrical Power and Mechatronics, Indonesian Institute of Sciences has tested its electric vehicle research prototype on the road, monitoring its voltage, current, temperature, time, vehicle velocity, motor speed, and SOC during the operation. Using this experimental data, the prediction model of battery SOC was built. Stepwise method considering multicollinearity was able to efficiently develops the battery prediction model that describes the multiple control parameters in relation to the characteristic values such as SOC. It was demonstrated that particle swarm optimization (PSO succesfully and efficiently calculated optimal control parameters to optimize evaluation item such as SOC based on the model.

Multi-Objective Predictive Balancing Control of Battery Packs Based on Predictive Current

Directory of Open Access Journals (Sweden)

Wenbiao Li

2016-04-01

Full Text Available Various balancing topology and control methods have been proposed for the inconsistency problem of battery packs. However, these strategies only focus on a single objective, ignore the mutual interaction among various factors and are only based on the external performance of the battery pack inconsistency, such as voltage balancing and state of charge (SOC balancing. To solve these problems, multi-objective predictive balancing control (MOPBC based on predictive current is proposed in this paper, namely, in the driving process of an electric vehicle, using predictive control to predict the battery pack output current the next time. Based on this information, the impact of the battery pack temperature caused by the output current can be obtained. Then, the influence is added to the battery pack balancing control, which makes the present degradation, temperature, and SOC imbalance achieve balance automatically due to the change of the output current the next moment. According to MOPBC, the simulation model of the balancing circuit is built with four cells in Matlab/Simulink. The simulation results show that MOPBC is not only better than the other traditional balancing control strategies but also reduces the energy loss in the balancing process.

Degradation Behaviour of Lithium-Ion Batteries based on Field Measured Frequency Regulation Mission Profile

DEFF Research Database (Denmark)

Stroe, Daniel Ioan; Swierczynski, Maciej Jozef; Stroe, Ana-Irina

2015-01-01

Energy storage systems based on Lithium-ion batteries have been proposed as an environmental friendly alternative to traditional conventional generating units for providing grid frequency regulation. One major challenge regarding the use of Lithium-ion batteries in such applications is their cost...... competitiveness in comparison to other storage technologies or with the traditional frequency regulation methods. In order to surpass this challenge and to allow for optimal sizing and proper use of the battery, accurate knowledge about the lifetime of the Lithium-ion battery and its degradation behaviour...... is required. This paper aims to investigate, based on a laboratory developed lifetime model, the degradation behaviour of the performance parameters (i.e., capacity and power capability) of a Lithium-ion battery cell when it is subjected to a field measured mission profile, which is characteristic...

UD-DKF-based Parameters on-line Identification Method and AEKF-Based SOC Estimation Strategy of Lithium-ion Battery

Directory of Open Access Journals (Sweden)

Xuanju Dang

2014-09-01

Full Text Available State of charge (SOC is a significant parameter for the Battery Management System (BMS. The accurate estimation of the SOC can not only guarantee the SOC remaining within a reasonable scope of work, but also prevent the battery from being over or deeply-charged to extend the lifespan of battery. In this paper, the third-order RC equivalent circuit model is adopted to describe cell characteristics and the dual Kalman filter (DKF is used online to identify model parameters for battery. In order to avoid the impacts of rounding error calculation leading to the estimation error matrix loss of non-negative qualitative which result in the filtering divergence phenomenon, the UD decomposition method is applied for filtering time and state updates simultaneously to enhance the stability of the algorithm, reduce the computational complexity and improve the high recognition accuracy. Based on the obtained model parameters, Adaptive Extended Kalman Filter (AEKF is introduced to online estimate the SOC of battery. The simulation and experimental results demonstrate that the established third-order RC equivalent circuit model is effective, and the SOC estimation has a higher precision.

Battery parameterisation based on differential evolution via a boundary evolution strategy

Science.gov (United States)

Yang, Guangya

2014-01-01

Attention has been given to the battery modelling in the electric engineering field following the current development of renewable energy and electrification of transportation. The establishment of the equivalent circuit model of the battery requires data preparation and parameterisation. Besides, as the equivalent circuit model is an abstract map of the battery electric characteristics, the determination of the possible ranges of parameters can be a challenging task. In this paper, an efficient yet easy to implement method is proposed to parameterise the equivalent circuit model of batteries utilising the advances of evolutionary algorithms (EAs). Differential evolution (DE) is selected and modified to parameterise an equivalent circuit model of lithium-ion batteries. A boundary evolution strategy (BES) is developed and incorporated into the DE to update the parameter boundaries during the parameterisation. The method can parameterise the model without extensive data preparation. In addition, the approach can also estimate the initial SOC and the available capacity. The efficiency of the approach is verified through two battery packs, one is an 8-cell battery module and one from an electrical vehicle.

Extensive EIS characterization of commercially available lithium polymer battery cell for performance modelling

DEFF Research Database (Denmark)

Stanciu, Tiberiu; Stroe, Daniel Loan; Teodorescu, Remus

2015-01-01

or degradation of an electrochemical system. Used for Lithium-ion (Li-ion) batteries, this method allows for a fast and accurate assessment of the battery's impedance at any working point, without modifying the state of the battery. The influence of the operating conditions, state of charge (SOC) and temperature...... on the performance of a commercially available 53 Ah Lithium polymer battery cell, manufactured by Kokam Co. Ltd., is investigated in laboratory experiments, at its beginning of life, by means of EIS. A data fitting algorithm was used to obtain the parameter values for the proposed equivalent electrical circuit......, which was further selected for the development of an accurate EIS based performance model for the chosen Li-ion battery cell....

Adaptive thermal modeling of Li-ion batteries

NARCIS (Netherlands)

Rad, M.S.; Danilov, D.L.; Baghalha, M.; Kazemeini, M.; Notten, P.H.L.

2013-01-01

An accurate thermal model to predict the heat generation in rechargeable batteries is an essential tool for advanced thermal management in high power applications, such as electric vehicles. For such applications, the battery materials’ details and cell design are normally not provided. In this work

Progress in electrolytes for rechargeable Li-based batteries and beyond

Directory of Open Access Journals (Sweden)

Qi Li

2016-04-01

Full Text Available Owing to almost unmatched volumetric energy density, Li-based batteries have dominated the portable electronic industry for the past 20 years. Not only will that continue, but they are also now powering plug-in hybrid electric vehicles and zero-emission vehicles. There is impressive progress in the exploration of electrode materials for lithium-based batteries because the electrodes (mainly the cathode are the limiting factors in terms of overall capacity inside a battery. However, more and more interests have been focused on the electrolytes, which determines the current (power density, the time stability, the reliability of a battery and the formation of solid electrolyte interface. This review will introduce five types of electrolytes for room temperature Li-based batteries including 1 non-aqueous electrolytes, 2 aqueous solutions, 3 ionic liquids, 4 polymer electrolytes, and 5 hybrid electrolytes. Besides, electrolytes beyond lithium-based systems such as sodium-, magnesium-, calcium-, zinc- and aluminum-based batteries will also be briefly discussed. Keywords: Electrolyte, Ionic liquid, Polymer, Hybrid, Battery

Depletion-of-Battery Attack: Specificity, Modelling and Analysis.

Science.gov (United States)

Shakhov, Vladimir; Koo, Insoo

2018-06-06

The emerging Internet of Things (IoT) has great potential; however, the societal costs of the IoT can outweigh its benefits. To unlock IoT potential, there needs to be improvement in the security of IoT applications. There are several standardization initiatives for sensor networks, which eventually converge with the Internet of Things. As sensor-based applications are deployed, security emerges as an essential requirement. One of the critical issues of wireless sensor technology is limited sensor resources, including sensor batteries. This creates a vulnerability to battery-exhausting attacks. Rapid exhaustion of sensor battery power is not only explained by intrusions, but can also be due to random failure of embedded sensor protocols. Thus, most wireless sensor applications, without tools to defend against rash battery exhausting, would be unable to function during prescribed times. In this paper, we consider a special type of threat, in which the harm is malicious depletion of sensor battery power. In contrast to the traditional denial-of-service attack, quality of service under the considered attack is not necessarily degraded. Moreover, the quality of service can increase up to the moment of the sensor set crashes. We argue that this is a distinguishing type of attack. Hence, the application of a traditional defense mechanism against this threat is not always possible. Therefore, effective methods should be developed to counter the threat. We first discuss the feasibility of rash depletion of battery power. Next, we propose a model for evaluation of energy consumption when under attack. Finally, a technique to counter the attack is discussed.

Optimal input shaping for Fisher identifiability of control-oriented lithium-ion battery models

Science.gov (United States)

Rothenberger, Michael J.

This dissertation examines the fundamental challenge of optimally shaping input trajectories to maximize parameter identifiability of control-oriented lithium-ion battery models. Identifiability is a property from information theory that determines the solvability of parameter estimation for mathematical models using input-output measurements. This dissertation creates a framework that exploits the Fisher information metric to quantify the level of battery parameter identifiability, optimizes this metric through input shaping, and facilitates faster and more accurate estimation. The popularity of lithium-ion batteries is growing significantly in the energy storage domain, especially for stationary and transportation applications. While these cells have excellent power and energy densities, they are plagued with safety and lifespan concerns. These concerns are often resolved in the industry through conservative current and voltage operating limits, which reduce the overall performance and still lack robustness in detecting catastrophic failure modes. New advances in automotive battery management systems mitigate these challenges through the incorporation of model-based control to increase performance, safety, and lifespan. To achieve these goals, model-based control requires accurate parameterization of the battery model. While many groups in the literature study a variety of methods to perform battery parameter estimation, a fundamental issue of poor parameter identifiability remains apparent for lithium-ion battery models. This fundamental challenge of battery identifiability is studied extensively in the literature, and some groups are even approaching the problem of improving the ability to estimate the model parameters. The first approach is to add additional sensors to the battery to gain more information that is used for estimation. The other main approach is to shape the input trajectories to increase the amount of information that can be gained from input

Optimal bidding strategy of battery storage in power markets considering performance based regulation and battery cycle life

DEFF Research Database (Denmark)

He, Guannan; Chen, Qixin; Kang, Chongqing

2016-01-01

to reduce the complexity of the model. This novel bidding model would help investor-owned battery storages better decide their bidding and operational schedules and investors to estimate the battery storage’s economic viability. The validity of the proposed model is proven by case study results....

Model-based prognostics for batteries which estimates useful life and uses a probability density function

Science.gov (United States)

Saha, Bhaskar (Inventor); Goebel, Kai F. (Inventor)

2012-01-01

This invention develops a mathematical model to describe battery behavior during individual discharge cycles as well as over its cycle life. The basis for the form of the model has been linked to the internal processes of the battery and validated using experimental data. Effects of temperature and load current have also been incorporated into the model. Subsequently, the model has been used in a Particle Filtering framework to make predictions of remaining useful life for individual discharge cycles as well as for cycle life. The prediction performance was found to be satisfactory as measured by performance metrics customized for prognostics for a sample case. The work presented here provides initial steps towards a comprehensive health management solution for energy storage devices.

Lithium-ion battery dynamic model for wide range of operating conditions

DEFF Research Database (Denmark)

Stroe, Ana-Irina; Stroe, Daniel-Ioan; Swierczynski, Maciej Jozef

2017-01-01

In order to analyze the dynamic behavior of a Lithium-ion (Li-ion) battery and to determine their suitability for various applications, battery models are needed. An equivalent electrical circuit model is the most common way of representing the behavior of a Li-ion battery. There are different...... characterization tests performed for a wide range of operating conditions (temperature, load current and state-of-charge) on a commercial available 13Ah high-power lithium titanate oxide battery cell. The obtained results were used to parametrize the proposed dynamic model of the battery cell. To assess...

An improved PNGV modeling and SOC estimation for lithium iron phosphate batteries

Science.gov (United States)

Li, Peng

2017-11-01

Because lithium iron phosphate battery has many advantages, it has been used more and more widely in the field of electric vehicle. The lithium iron phosphate battery, presents the improved PNGV model, and the batteries charge discharge characteristics and pulse charge discharge experiments, identification of parameters of the battery model by interpolation and least square fitting method, to achieve a more accurate modeling of lithium iron phosphate battery, and the extended Calman filter algorithm (EKF) is completed state nuclear power battery (SOC) estimate.

A method for state-of-charge estimation of Li-ion batteries based on multi-model switching strategy

International Nuclear Information System (INIS)

Wang, Yujie; Zhang, Chenbin; Chen, Zonghai

2015-01-01

Highlights: • Build a multi-model switching SOC estimate method for Li-ion batteries. • Build an improved interpretative structural modeling method for model switching. • The feedback strategy of bus delay is applied to improve the real-time performance. • The EKF method is used for SOC estimation to improve the estimated accuracy. - Abstract: The accurate state-of-charge (SOC) estimation and real-time performance are critical evaluation indexes for Li-ion battery management systems (BMS). High accuracy algorithms often take long program execution time (PET) in the resource-constrained embedded application systems, which will undoubtedly lead to the decrease of the time slots of other processes, thereby reduce the overall performance of BMS. Considering the resource optimization and the computational load balance, this paper proposes a multi-model switching SOC estimation method for Li-ion batteries. Four typical battery models are employed to build a close-loop SOC estimation system. The extended Kalman filter (EKF) method is employed to eliminate the effect of the current noise and improve the accuracy of SOC. The experiments under dynamic current conditions are conducted to verify the accuracy and real-time performance of the proposed method. The experimental results indicate that accurate estimation results and reasonable PET can be obtained by the proposed method

Particle-filtering-based estimation of maximum available power state in Lithium-Ion batteries

International Nuclear Information System (INIS)

Burgos-Mellado, Claudio; Orchard, Marcos E.; Kazerani, Mehrdad; Cárdenas, Roberto; Sáez, Doris

2016-01-01

Highlights: • Approach to estimate the state of maximum power available in Lithium-Ion battery. • Optimisation problem is formulated on the basis of a non-linear dynamic model. • Solutions of the optimisation problem are functions of state of charge estimates. • State of charge estimates computed using particle filter algorithms. - Abstract: Battery Energy Storage Systems (BESS) are important for applications related to both microgrids and electric vehicles. If BESS are used as the main energy source, then it is required to include adequate procedures for the estimation of critical variables such as the State of Charge (SoC) and the State of Health (SoH) in the design of Battery Management Systems (BMS). Furthermore, in applications where batteries are exposed to high charge and discharge rates it is also desirable to estimate the State of Maximum Power Available (SoMPA). In this regard, this paper presents a novel approach to the estimation of SoMPA in Lithium-Ion batteries. This method formulates an optimisation problem for the battery power based on a non-linear dynamic model, where the resulting solutions are functions of the SoC. In the battery model, the polarisation resistance is modelled using fuzzy rules that are function of both SoC and the discharge (charge) current. Particle filtering algorithms are used as an online estimation technique, mainly because these algorithms allow approximating the probability density functions of the SoC and SoMPA even in the case of non-Gaussian sources of uncertainty. The proposed method for SoMPA estimation is validated using the experimental data obtained from an experimental setup designed for charging and discharging the Lithium-Ion batteries.

Modeling the Performance and Cost of Lithium-Ion Batteries for Electric-Drive Vehicles - SECOND EDITION

Energy Technology Data Exchange (ETDEWEB)

Nelson, Paul A. [Argonne National Lab. (ANL), Argonne, IL (United States); Gallagher, Kevin G. [Argonne National Lab. (ANL), Argonne, IL (United States); Bloom, Ira D. [Argonne National Lab. (ANL), Argonne, IL (United States); Dees, Dennis W. [Argonne National Lab. (ANL), Argonne, IL (United States)

2012-01-01

This report details the Battery Performance and Cost model (BatPaC) developed at Argonne National Laboratory for lithium-ion battery packs used in automotive transportation. The model designs the battery for a specified power, energy, and type of vehicle battery. The cost of the designed battery is then calculated by accounting for every step in the lithium-ion battery manufacturing process. The assumed annual production level directly affects each process step. The total cost to the original equipment manufacturer calculated by the model includes the materials, manufacturing, and warranty costs for a battery produced in the year 2020 (in 2010 US$). At the time this report is written, this calculation is the only publicly available model that performs a bottom-up lithium-ion battery design and cost calculation. Both the model and the report have been publicly peer-reviewed by battery experts assembled by the U.S. Environmental Protection Agency. This report and accompanying model include changes made in response to the comments received during the peer-review. The purpose of the report is to document the equations and assumptions from which the model has been created. A user of the model will be able to recreate the calculations and perhaps more importantly, understand the driving forces for the results. Instructions for use and an illustration of model results are also presented. Almost every variable in the calculation may be changed by the user to represent a system different from the default values pre-entered into the program. The distinct advantage of using a bottom-up cost and design model is that the entire power-to-energy space may be traversed to examine the correlation between performance and cost. The BatPaC model accounts for the physical limitations of the electrochemical processes within the battery. Thus, unrealistic designs are penalized in energy density and cost, unlike cost models based on linear extrapolations. Additionally, the consequences on

Fuzzy logic-based battery charge controller

International Nuclear Information System (INIS)

Daoud, A.; Midoun, A.

2006-01-01

Photovoltaic power system are generally classified according to their functional and operational requirements, their component configurations, and how the equipment is connected to other power sources and electrical loads, photovoltaic systems can be designed to provide DC and/or AC power service, can operate interconnected with or independent of the utility grid, and can be connected with other energy sources and energy storage systems. Batteries are often used in PV systems for the purpose of storing energy produced by the PV array during the day, and to supply it to electrical loads as needed (during the night and periods of cloudy weather). The lead acid battery, although know for more than one hundred years, has currently offered the best response in terms of price, energetic efficiency and lifetime. The main function of controller or regulator in PV system is too fully charge the battery without permitting overcharge while preventing reverse current flow at night. If a no-self-regulating solar array is connected to lead acid batteries with no overcharge protection, battery life will be compromised. Simple controllers contain a transistor that disconnects or reconnects the PV in the charging circuit once a pre-set voltage is reached. More sophisticated controllers utilize pulse with modulation (PWM) to assure the battery is being fully charged. The first 70% to 80% of battery capacity is easily replaced, but the last 20% to 30% requires more attention and therefore more complexity. This complexity is avoided by using a skilled operators experience in the form of the rules. Thus a fuzzy control system seeks to control the battery that cannot be controlled well by a conventional control such as PID, PD, PI etc., due to the unavailability of an accurate mathematical model of the battery. In this paper design of an intelligent battery charger, in which the control algorithm is implemented with fuzzy logic is discussed. The digital architecture is implemented with

Safety modelling and testing of lithium-ion batteries in electrified vehicles

Science.gov (United States)

Deng, Jie; Bae, Chulheung; Marcicki, James; Masias, Alvaro; Miller, Theodore

2018-04-01

To optimize the safety of batteries, it is important to understand their behaviours when subjected to abuse conditions. Most early efforts in battery safety modelling focused on either one battery cell or a single field of interest such as mechanical or thermal failure. These efforts may not completely reflect the failure of batteries in automotive applications, where various physical processes can take place in a large number of cells simultaneously. In this Perspective, we review modelling and testing approaches for battery safety under abuse conditions. We then propose a general framework for large-scale multi-physics modelling and experimental work to address safety issues of automotive batteries in real-world applications. In particular, we consider modelling coupled mechanical, electrical, electrochemical and thermal behaviours of batteries, and explore strategies to extend simulations to the battery module and pack level. Moreover, we evaluate safety test approaches for an entire range of automotive hardware sets from cell to pack. We also discuss challenges in building this framework and directions for its future development.

Integrated modeling for the cyclic behavior of high power Li-ion batteries under extended operating conditions

International Nuclear Information System (INIS)

Miranda, Á.G.; Hong, C.W.

2013-01-01

Highlights: • Redefine the traditional concepts of state of charge modeling. • Accurate non-intrusive extraction method of an integrated battery model. • Indexes of performance can be employed to compare different types of batteries. • High power electrical battery model dependent on current and temperature effects. - Abstract: The dynamic thermal and electrical behavior of high power LiFePO 4 cathode-type Li-ion batteries is studied with extended considerations such as demanded current ranging from 12 to 30 A, battery temperatures ranging from 283 to 313 K and a redefinition of the concept of state of charge during cycling conditions. The equivalent electrical model, consisting of a series resistance, a parallel resistance–capacitor, a voltage source and state of charge calculators, can be improved with the addition of current and temperature gains for each element. In addition, a non-intrusively-obtained alternative thermal model extraction is proposed to uncouple from the experimental battery temperature based on electrochemical research found in the literature. This improved model extraction for high power cylindrical batteries can achieve a temperature and voltage relative runtime error in the range of 1% and 5% in average, respectively. The effects of lithium concentration in the anode and cathode are accurately predicted with state of charge accelerators, which vary linearly with temperature. Aiming for a power systems environment, the integrated battery model is built and validated experimentally to demonstrate its accurate prediction. This improved integrated battery model can be employed for battery stack simulations, improved state of charge algorithm testing and optimization of hybrid systems - with a light computational demand. Finally, a performance index radar plot is proposed to conveniently compare electrical and thermal properties of different types of batteries

An adaptive model for vanadium redox flow battery and its application for online peak power estimation

Science.gov (United States)

Wei, Zhongbao; Meng, Shujuan; Tseng, King Jet; Lim, Tuti Mariana; Soong, Boon Hee; Skyllas-Kazacos, Maria

2017-03-01

An accurate battery model is the prerequisite for reliable state estimate of vanadium redox battery (VRB). As the battery model parameters are time varying with operating condition variation and battery aging, the common methods where model parameters are empirical or prescribed offline lacks accuracy and robustness. To address this issue, this paper proposes to use an online adaptive battery model to reproduce the VRB dynamics accurately. The model parameters are online identified with both the recursive least squares (RLS) and the extended Kalman filter (EKF). Performance comparison shows that the RLS is superior with respect to the modeling accuracy, convergence property, and computational complexity. Based on the online identified battery model, an adaptive peak power estimator which incorporates the constraints of voltage limit, SOC limit and design limit of current is proposed to fully exploit the potential of the VRB. Experiments are conducted on a lab-scale VRB system and the proposed peak power estimator is verified with a specifically designed "two-step verification" method. It is shown that different constraints dominate the allowable peak power at different stages of cycling. The influence of prediction time horizon selection on the peak power is also analyzed.

Cell design concepts for aqueous lithium-oxygen batteries: A model-based assessment

Science.gov (United States)

Grübl, Daniel; Bessler, Wolfgang G.

2015-11-01

Seven cell design concepts for aqueous (alkaline) lithium-oxygen batteries are investigated using a multi-physics continuum model for predicting cell behavior and performance in terms of the specific energy and specific power. Two different silver-based cathode designs (a gas diffusion electrode and a flooded cathode) and three different separator designs (a porous separator, a stirred separator chamber, and a redox-flow separator) are compared. Cathode and separator thicknesses are varied over a wide range (50 μm-20 mm) in order to identify optimum configurations. All designs show a considerable capacity-rate effect due to spatiotemporally inhomogeneous precipitation of solid discharge product LiOH·H2O. In addition, a cell design with flooded cathode and redox-flow separator including oxygen uptake within the external tank is suggested. For this design, the model predicts specific power up to 33 W/kg and specific energy up to 570 Wh/kg (gravimetric values of discharged cell including all cell components and catholyte except housing and piping).

Prediction of lithium-ion battery capacity with metabolic grey model

International Nuclear Information System (INIS)

Chen, Lin; Lin, Weilong; Li, Junzi; Tian, Binbin; Pan, Haihong

2016-01-01

Given the popularity of Lithium-ion batteries in EVs (electric vehicles), predicting the capacity quickly and accurately throughout a battery's full life-time is still a challenging issue for ensuring the reliability of EVs. This paper proposes an approach in predicting the varied capacity with discharge cycles based on metabolic grey theory and consider issues from two perspectives: 1) three metabolic grey models will be presented, including MGM (metabolic grey model), MREGM (metabolic Residual-error grey model), and MMREGM (metabolic Markov-residual-error grey model); 2) the universality of these models will be explored under different conditions (such as various discharge rates and temperatures). Furthermore, the research findings in this paper demonstrate the excellent performance of the prediction depending on the three models; however, the precision of the MREGM model is inferior compared to the others. Therefore, we have obtained the conclusion in which the MGM model and the MMREGM model have excellent performances in predicting the capacity under a variety of load conditions, even using few data points for modeling. Also, the universality of the metabolic grey prediction theory is verified by predicting the capacity of batteries under different discharge rates and different temperatures. - Highlights: • The metabolic mechanism is introduced in a grey system for capacity prediction. • Three metabolic grey models are presented and studied. • The universality of these models under different conditions is assessed. • A few data points are required for predicting the capacity with these models.

Effect of energy-regenerative braking on electric vehicle battery thermal management and control method based on simulation investigation

International Nuclear Information System (INIS)

Huang, Jingying; Qin, Datong; Peng, Zhiyuan

2015-01-01

Highlights: • A two-degree-of-freedom lumped thermal model is developed for battery. • The battery thermal model is integrated with vehicle driving model. • Real-time battery thermal responses is obtained. • Active control of current by regenerative braking ratio adjustment is proposed. • More energy is recovered with smaller battery temperature rise. - Abstract: Battery thermal management is important for the safety and reliability of electric vehicle. Based on the parameters obtained from battery hybrid pulse power characterization test, a two-degree-of-freedom lumped thermal model is established. The battery model is then integrated with vehicle driving model to simulate real-time battery thermal responses. An active control method is proposed to reduce heat generation due to regenerative braking. The proposed control method not only subjects to the braking safety regulation, but also adjusts the regenerative braking ratio through a fuzzy controller. By comparing with other regenerative braking scenarios, the effectiveness of the proposed strategy has been validated. According to the results, the proposed control strategy suppresses battery temperature rise by modifying the charge current due to regenerative braking. The overlarge components of current are filtered out whereas the small ones are magnified. Therefore, with smaller battery temperature rise, more energy is recovered. Compared to the traditional passive heat dissipating, the proposed active methodology is feasible and provides a novel solution for electric vehicle battery thermal management.

Impedance based time-domain modeling of lithium-ion batteries: Part I

Science.gov (United States)

Gantenbein, Sophia; Weiss, Michael; Ivers-Tiffée, Ellen

2018-03-01

This paper presents a novel lithium-ion cell model, which simulates the current voltage characteristic as a function of state of charge (0%-100%) and temperature (0-30 °C). It predicts the cell voltage at each operating point by calculating the total overvoltage from the individual contributions of (i) the ohmic loss η0, (ii) the charge transfer loss of the cathode ηCT,C, (iii) the charge transfer loss and the solid electrolyte interface loss of the anode ηSEI/CT,A, and (iv) the solid state and electrolyte diffusion loss ηDiff,A/C/E. This approach is based on a physically meaningful equivalent circuit model, which is parametrized by electrochemical impedance spectroscopy and time domain measurements, covering a wide frequency range from MHz to μHz. The model is exemplarily parametrized to a commercial, high-power 350 mAh graphite/LiNiCoAlO2-LiCoO2 pouch cell and validated by continuous discharge and charge curves at varying temperature. For the first time, the physical background of the model allows the operator to draw conclusions about the performance-limiting factor at various operating conditions. Not only can the model help to choose application-optimized cell characteristics, but it can also support the battery management system when taking corrective actions during operation.

Machine Learning Based Diagnosis of Lithium Batteries

Science.gov (United States)

Ibe-Ekeocha, Chinemerem Christopher

The depletion of the world's current petroleum reserve, coupled with the negative effects of carbon monoxide and other harmful petrochemical by-products on the environment, is the driving force behind the movement towards renewable and sustainable energy sources. Furthermore, the growing transportation sector consumes a significant portion of the total energy used in the United States. A complete electrification of this sector would require a significant development in electric vehicles (EVs) and hybrid electric vehicles (HEVs), thus translating to a reduction in the carbon footprint. As the market for EVs and HEVs grows, their battery management systems (BMS) need to be improved accordingly. The BMS is not only responsible for optimally charging and discharging the battery, but also monitoring battery's state of charge (SOC) and state of health (SOH). SOC, similar to an energy gauge, is a representation of a battery's remaining charge level as a percentage of its total possible charge at full capacity. Similarly, SOH is a measure of deterioration of a battery; thus it is a representation of the battery's age. Both SOC and SOH are not measurable, so it is important that these quantities are estimated accurately. An inaccurate estimation could not only be inconvenient for EV consumers, but also potentially detrimental to battery's performance and life. Such estimations could be implemented either online, while battery is in use, or offline when battery is at rest. This thesis presents intelligent online SOC and SOH estimation methods using machine learning tools such as artificial neural network (ANN). ANNs are a powerful generalization tool if programmed and trained effectively. Unlike other estimation strategies, the techniques used require no battery modeling or knowledge of battery internal parameters but rather uses battery's voltage, charge/discharge current, and ambient temperature measurements to accurately estimate battery's SOC and SOH. The developed

Electrochemical modeling and performance evaluation of a new ammonia-based battery thermal management system for electric and hybrid electric vehicles

International Nuclear Information System (INIS)

Al-Zareer, Maan; Dincer, Ibrahim; Rosen, Marc A.

2017-01-01

The operating temperatures of lithium ion battery packs in electrical vehicles and hybrid electrical vehicles need to be maintained in an optimum range for better performance and longer battery life. This paper proposes a new battery pack cooling system that utilizes the low saturation temperature of the fuel in ammonia based future hybrid electric vehicles. In the proposed cooling system, the batteries are partially submerged in to the liquid ammonia, and the liquid ammonia cools the battery by absorbing the heat and evaporating and the ammonia vapor cools the part of the battery not covered by liquid ammonia. The relationships between the performance of the battery cooling system and the maximum temperature (and the temperature distribution) in the battery are investigated for practical applications. The effect of the length of the battery that is submerged in to the liquid ammonia on the thermal performance of battery is studied and evaluated. The present results show that the proposed ammonia based cooling system offers a unique opportunity to maintain the operating temperature of the battery in an optimum range for consecutive charging and discharging phases at a high rate of 7.5C.

Thermal modelling of Li-ion polymer battery for electric vehicle drive cycles

Science.gov (United States)

Chacko, Salvio; Chung, Yongmann M.

2012-09-01

Time-dependent, thermal behaviour of a lithium-ion (Li-ion) polymer cell has been modelled for electric vehicle (EV) drive cycles with a view to developing an effective battery thermal management system. The fully coupled, three-dimensional transient electro-thermal model has been implemented based on a finite volume method. To support the numerical study, a high energy density Li-ion polymer pouch cell was tested in a climatic chamber for electric load cycles consisting of various charge and discharge rates, and a good agreement was found between the model predictions and the experimental data. The cell-level thermal behaviour under stressful conditions such as high power draw and high ambient temperature was predicted with the model. A significant temperature increase was observed in the stressful condition, corresponding to a repeated acceleration and deceleration, indicating that an effective battery thermal management system would be required to maintain the optimal cell performance and also to achieve a full battery lifesapn.

Lifetime modelling of lead acid batteries

Energy Technology Data Exchange (ETDEWEB)

Bindner, H.; Cronin, T.; Lundsager, P.

2005-04-01

The performance and lifetime of energy storage in batteries are an important part of many renewable based energy systems. Not only do batteries impact on the system performance but they are also a significant expenditure when considering the whole life cycle costs. Poor prediction of lifetime can, therefore, lead to uncertainty in the viability of the system in the long term. This report details the work undertaken to investigate and develop two different battery life prediction methodologies with specific reference to their use in hybrid renewable energy systems. Alongside this, results from battery tests designed to exercise batteries in similar modes to those that they experience in hybrid systems have also been analysed. These have yielded battery specific parameters for use in the prediction software and the first results in the validation process of the software are also given. This work has been part of the European Union Benchmarking research project (ENK6-CT-2001-80576), funded by the European Union, the United States and Australian governments together with other European states and other public and private financing bodies. The project has concentrated on lead acid batteries as this technology is the most commonly used. Through this work the project partner institutions have intended to provide useful tools to improve the design capabilities of organizations, private and public, in remote power systems. (au)

Evaluation of a Novel BEV Concept Based on Fixed and Swappable Li-Ion Battery Packs

DEFF Research Database (Denmark)

Barreras, Jorge Varela; Pinto, Claudio; de Castro, Ricardo

2016-01-01

-based ownership models to distribute the cost of the large battery pack over the vehicle lifetime. A methodology is proposed for the analysis and evaluation of the proposed concept in comparison with a direct owned nonswappable single-pack BEV, proving that significant improvements on city fuel economy (up to 14......In this paper, a novel battery electric vehicle (BEV) concept based on a small fixed and a big swappable Li-ion battery pack is proposed in order to achieve longer range, lower initial purchase priceand lower energy consumption at short ranges. For short ranges, the BEV is only powered...... by the relatively small-fixed battery pack, without the large swappable battery pack. In this way, the mass of the vehicle is reduced and, therefore, the energy consumed per unit distance is improved. For higher ranges, the BEV is powered by both battery packs. This concept allows the introduction of subscription...

A dynamic capacity degradation model and its applications considering varying load for a large format Li-ion battery

International Nuclear Information System (INIS)

Ouyang, Minggao; Feng, Xuning; Han, Xuebing; Lu, Languang; Li, Zhe; He, Xiangming

2016-01-01

Highlights: • A dynamic capacity degradation model for large format Li-ion battery is proposed. • The change of the model parameters directly link with the degradation mechanisms. • The model can simulate the fading behavior of Li-ion battery under varying loads. • The model can help evaluate the longevity of a battery system under specific load. • The model can help predict the evolution of cell variations within a battery pack. - Abstract: The capacity degradation of the lithium ion battery should be well predicted during battery system design. Therefore, high-fidelity capacity degradation models that are suitable for the task of capacity prediction are required. This paper proposes a novel capacity degradation model that can simulate the degradation dynamics under varying working conditions for large-format lithium ion batteries. The degradation model is built based on a mechanistic and prognostic model (MPM) whose parameters are closely linked with the degradation mechanisms of lithium ion batteries. Chemical kinetics was set to drive the parameters of the MPM to change as capacity degradation continues. With the dynamic parameters of the MPM, the capacity predicted by the degradation model decreases as the cycle continues. Accelerated aging tests were conducted on three types of commercial lithium ion batteries to calibrate the capacity degradation model. The good fit with the experimental data indicates that the model can capture the degradation mechanisms well for different types of commercial lithium ion batteries. Furthermore, the calibrated model can be used to (1) evaluate the longevity of a battery system under a specific working load and (2) predict the evolution of cell variations within a battery pack when different cell works at different conditions. Correlated applications are discussed using the calibrated degradation model.

Prediction Model and Principle of End-of-Life Threshold for Lithium Ion Batteries Based on Open Circuit Voltage Drifts

International Nuclear Information System (INIS)

Cui, Yingzhi; Yang, Jie; Du, Chunyu; Zuo, Pengjian; Gao, Yunzhi; Cheng, Xinqun; Ma, Yulin; Yin, Geping

2017-01-01

Highlights: •Open circuit voltage evolution over ageing of lithium ion batteries is deciphered. •The mechanism responsible for the end-of-life (EOL) threshold is elaborated. •A new prediction model of EOL threshold with improved accuracy is developed. •This EOL prediction model is promising for the applications in electric vehicles. -- Abstract: The end-of-life (EOL) of a lithium ion battery (LIB) is defined as the time point when the LIB can no longer provide sufficient power or energy to accomplish its intended function. Generally, the EOL occurs abruptly when the degradation of a LIB reaches the threshold. Therefore, current prediction methods of EOL by extrapolating the early degradation behavior often result in significant errors. To address this problem, this paper analyzes the reason for the EOL threshold of a LIB with shallow depth of discharge. It is found that the sudden appearance of EOL threshold results from the drift of open circuit voltage (OCV) at the end of both shallow depth and full discharges. Further, a new EOL threshold prediction model with highly improved accuracy is developed based on the OCV drifts and their evolution mechanism, which can effectively avoid the misjudgment of EOL threshold. The accuracy of this EOL threshold prediction model is verified by comparing with experimental results. The EOL threshold prediction model can be applied to other battery chemistry systems and its possible application in electric vehicles is finally discussed.

Lithium-ion Battery Electrothermal Model, Parameter Estimation, and Simulation Environment

Directory of Open Access Journals (Sweden)

Simone Orcioni

2017-03-01

Full Text Available The market for lithium-ion batteries is growing exponentially. The performance of battery cells is growing due to improving production technology, but market request is growing even more rapidly. Modeling and characterization of single cells and an efficient simulation environment is fundamental for the development of an efficient battery management system. The present work is devoted to defining a novel lumped electrothermal circuit of a single battery cell, the extraction procedure of the parameters of the single cell from experiments, and a simulation environment in SystemC-WMS for the simulation of a battery pack. The electrothermal model of the cell was validated against experimental measurements obtained in a climatic chamber. The model is then used to simulate a 48-cell battery, allowing statistical variations among parameters. The different behaviors of the cells in terms of state of charge, current, voltage, or heat flow rate can be observed in the results of the simulation environment.

Depletion-of-Battery Attack: Specificity, Modelling and Analysis

Directory of Open Access Journals (Sweden)

Vladimir Shakhov

2018-06-01

Full Text Available The emerging Internet of Things (IoT has great potential; however, the societal costs of the IoT can outweigh its benefits. To unlock IoT potential, there needs to be improvement in the security of IoT applications. There are several standardization initiatives for sensor networks, which eventually converge with the Internet of Things. As sensor-based applications are deployed, security emerges as an essential requirement. One of the critical issues of wireless sensor technology is limited sensor resources, including sensor batteries. This creates a vulnerability to battery-exhausting attacks. Rapid exhaustion of sensor battery power is not only explained by intrusions, but can also be due to random failure of embedded sensor protocols. Thus, most wireless sensor applications, without tools to defend against rash battery exhausting, would be unable to function during prescribed times. In this paper, we consider a special type of threat, in which the harm is malicious depletion of sensor battery power. In contrast to the traditional denial-of-service attack, quality of service under the considered attack is not necessarily degraded. Moreover, the quality of service can increase up to the moment of the sensor set crashes. We argue that this is a distinguishing type of attack. Hence, the application of a traditional defense mechanism against this threat is not always possible. Therefore, effective methods should be developed to counter the threat. We first discuss the feasibility of rash depletion of battery power. Next, we propose a model for evaluation of energy consumption when under attack. Finally, a technique to counter the attack is discussed.

Using Neutron-based techniques to investigate battery behaviour

International Nuclear Information System (INIS)

Pramudita, James C.; Goonetilleke, Damien; Sharma, Neeraj; Peterson, Vanessa K.

2016-01-01

The extensive use of portable electronic devices has given rise to increasing demand for reliable high energy density storage in the form of batteries. Today, lithium-ion batteries (LIBs) are the leading technology as they offer high energy density and relatively long lifetimes. Despite their widespread adoption, Li-ion batteries still suffer from significant degradation in their performance over time. The most obvious degradation in lithium-ion battery performance is capacity fade – where the capacity of the battery reduces after extended cycling. This talk will focus on how in situ time-resolved neutron powder diffraction (NPD) can be used to gain a better understanding of the structural changes which contribute to the observed capacity fade. The commercial batteries studied each feature different electrochemical and storage histories that are precisely known, allowing us to elucidate the tell-tale signs of battery degradation using NPD and relate these to battery history. Moreover, this talk will also showcase the diverse use of other neutron-based techniques such as neutron imaging to study electrolyte concentrations in lead-acid batteries, and the use of quasi-elastic neutron scattering to study Na-ion dynamics in sodium-ion batteries.

Modeling, Design and Simulation of Stand-Alone Photovoltaic Power Systems with Battery Storage

Directory of Open Access Journals (Sweden)

Abd Essalam BADOUD

2013-06-01

Full Text Available Stand alone renewable energy based on photovoltaic systems accompanied with battery storage system are beginning to play an important role over the world to supply power to remote areas. The objective of the study reported in this paper is to elaborate and design a bond graphs model for sizing stand-alone domestic solar photovoltaic electricity systems and simulating the performance of the systems in a tropical climate. The systems modelled consist of an array of PV modules, a lead-acid battery, and a number of direct current appliances. This paper proposes the combination of lead acid battery system with a typical stand alone photovoltaic energy system under variable loads. The main activities of this work purpose to establish library graphical models for each individual component of standalone photovoltaic system. Control strategy has been considered to achieve permanent power supply to the load via photovoltaic/battery based on the power available from the sun. The complete model was simulated under two testing including sunny and cloudy conditions. Simulation of the system using Symbols software was performed and the results of simulation show the superior stable control system and high efficiency. These results have been contrasted with real measured data from a measurement campaign plant carried on electrical engineering laboratory of Grenoble using various interconnection schemes are presented.

Fabrication, characterization, and modeling of a biodegradable battery for transient electronics

Science.gov (United States)

Edupuganti, Vineet; Solanki, Raj

2016-12-01

Traditionally, emphasis has been placed on durable, long-lasting electronics. However, electronics that are meant to intentionally degrade over time can actually have significant practical applications. Biodegradable, or transient, electronics would open up opportunities in the field of medical implants, where the need for surgical removal of devices could be eliminated. Environmental sensors and, eventually, consumer electronics would also greatly benefit from this technology. An essential component of transient electronics is the battery, which serves as a biodegradable power source. This work involves the fabrication, characterization, and modeling of a magnesium-based biodegradable battery. Galvanostatic discharge tests show that an anode material of magnesium alloy AZ31 extends battery lifetime by over six times, as compared to pure magnesium. With AZ31, the maximum power and capacity of the fabricated device are 67 μW and 5.2 mAh, respectively, though the anode area is just 0.8 cm2. The development of an equivalent circuit model provided insight into the battery's behavior by extracting fitting parameters from experimental data. The model can accurately simulate device behavior, taking into account its intentional degradation. The size of the device and the power it produces are in accordance with typical levels for low-power transient systems.

Numerical simulation and optimization of nickel-hydrogen batteries

Science.gov (United States)

Yu, Li-Jun; Qin, Ming-Jun; Zhu, Peng; Yang, Li

2008-05-01

A three-dimensional, transient numerical model of an individual pressure vessel (IPV) nickel-hydrogen battery has been developed based on energy conservation law, mechanisms of heat and mass transfer, and electrochemical reactions in the battery. The model, containing all components of a battery including the battery shell, was utilized to simulate the transient temperature of the battery, using computational fluid dynamics (CFD) technology. The comparison of the model prediction and experimental data shows a good agreement, which means that the present model can be used for the engineering design and parameter optimization of nickel-hydrogen batteries in aerospace power systems. Two kinds of optimization schemes were provided and evaluated by the simulated temperature field. Based on the model, the temperature simulation during five successive periods in a designed space battery was conducted and the simulation results meet the requirement of safe operation.

A comparative study of three model-based algorithms for estimating state-of-charge of lithium-ion batteries under a new combined dynamic loading profile

International Nuclear Information System (INIS)

Yang, Fangfang; Xing, Yinjiao; Wang, Dong; Tsui, Kwok-Leung

2016-01-01

Highlights: • Three different model-based filtering algorithms for SOC estimation are compared. • A combined dynamic loading profile is proposed to evaluate the three algorithms. • Robustness against uncertainty of initial states of SOC estimators are investigated. • Battery capacity degradation is considered in SOC estimation. - Abstract: Accurate state-of-charge (SOC) estimation is critical for the safety and reliability of battery management systems in electric vehicles. Because SOC cannot be directly measured and SOC estimation is affected by many factors, such as ambient temperature, battery aging, and current rate, a robust SOC estimation approach is necessary to be developed so as to deal with time-varying and nonlinear battery systems. In this paper, three popular model-based filtering algorithms, including extended Kalman filter, unscented Kalman filter, and particle filter, are respectively used to estimate SOC and their performances regarding to tracking accuracy, computation time, robustness against uncertainty of initial values of SOC, and battery degradation, are compared. To evaluate the performances of these algorithms, a new combined dynamic loading profile composed of the dynamic stress test, the federal urban driving schedule and the US06 is proposed. The comparison results showed that the unscented Kalman filter is the most robust to different initial values of SOC, while the particle filter owns the fastest convergence ability when an initial guess of SOC is far from a true initial SOC.

Generalized Characterization Methodology for Performance Modelling of Lithium-Ion Batteries

DEFF Research Database (Denmark)

Stroe, Daniel Loan; Swierczynski, Maciej Jozef; Stroe, Ana-Irina

2016-01-01

Lithium-ion (Li-ion) batteries are complex energy storage devices with their performance behavior highly dependent on the operating conditions (i.e., temperature, load current, and state-of-charge (SOC)). Thus, in order to evaluate their techno-economic viability for a certain application, detailed...... information about Li-ion battery performance behavior becomes necessary. This paper proposes a comprehensive seven-step methodology for laboratory characterization of Li-ion batteries, in which the battery’s performance parameters (i.e., capacity, open-circuit voltage (OCV), and impedance) are determined...... and their dependence on the operating conditions are obtained. Furthermore, this paper proposes a novel hybrid procedure for parameterizing the batteries’ equivalent electrical circuit (EEC), which is used to emulate the batteries’ dynamic behavior. Based on this novel parameterization procedure, the performance model...

Mathematical modeling of the nickel/metal hydride battery system

Energy Technology Data Exchange (ETDEWEB)

Paxton, Blaine Kermit [Univ. of California, Berkeley, CA (United States). Dept. of Chemical Engineering

1995-09-01

A group of compounds referred to as metal hydrides, when used as electrode materials, is a less toxic alternative to the cadmium hydroxide electrode found in nickel/cadmium secondary battery systems. For this and other reasons, the nickel/metal hydride battery system is becoming a popular rechargeable battery for electric vehicle and consumer electronics applications. A model of this battery system is presented. Specifically the metal hydride material, LaNi{sub 5}H{sub 6}, is chosen for investigation due to the wealth of information available in the literature on this compound. The model results are compared to experiments found in the literature. Fundamental analyses as well as engineering optimizations are performed from the results of the battery model. In order to examine diffusion limitations in the nickel oxide electrode, a ``pseudo 2-D model`` is developed. This model allows for the theoretical examination of the effects of a diffusion coefficient that is a function of the state of charge of the active material. It is found using present data from the literature that diffusion in the solid phase is usually not an important limitation in the nickel oxide electrode. This finding is contrary to the conclusions reached by other authors. Although diffusion in the nickel oxide active material is treated rigorously with the pseudo 2-D model, a general methodology is presented for determining the best constant diffusion coefficient to use in a standard one-dimensional battery model. The diffusion coefficients determined by this method are shown to be able to partially capture the behavior that results from a diffusion coefficient that varies with the state of charge of the active material.

Thermal modeling of cylindrical LiFePO4 batteries

OpenAIRE

Shadman Rad, M.; Danilov, D.L.; Baghalha, M.; Kazemeini, M.; Notten, P.H.L.

2013-01-01

Thermal management of Li-ion batteries is important because of the high energy content and the risk of rapid temperature development in the high current range. Reliable and safe operation of these batteries is seriously endangered by high temperatures. It is important to have a simple but accurate model to evaluate the thermal behavior of batteries under a variety of operating conditions and be able to predict the internal temperature as well. To achieve this goal, a radial-axial model is dev...

Multiphysics Based Thermal Modeling of a Pouch Lithium-Ion Battery Cell for the Development of Pack Level Thermal Management System

DEFF Research Database (Denmark)

Khan, Mohammad Rezwan; Kær, Søren Knudsen

2016-01-01

The research is focused on the development of a three-dimensional cell level multiphysics battery thermal model. The primary aim is to represent the cooling mechanism inside the unit cell battery pack. It is accomplished through the coupling of heat transfer and computational fluid dynamics (CFD......) physics. A lumped value of heat generation (HG) inside the battery cell is used. It stems from isothermal calorimeter experiment. HG depends on current rate and the corresponding operating temperature. It is demonstrated that the developed model provides a deeper understanding of the thermal spatio......-temporal behavior of Li-ion battery in different operating conditions....

Entropy-Based Voltage Fault Diagnosis of Battery Systems for Electric Vehicles

Directory of Open Access Journals (Sweden)

Peng Liu

2018-01-01

Full Text Available The battery is a key component and the major fault source in electric vehicles (EVs. Ensuring power battery safety is of great significance to make the diagnosis more effective and predict the occurrence of faults, for the power battery is one of the core technologies of EVs. This paper proposes a voltage fault diagnosis detection mechanism using entropy theory which is demonstrated in an EV with a multiple-cell battery system during an actual operation situation. The preliminary analysis, after collecting and preprocessing the typical data periods from Operation Service and Management Center for Electric Vehicle (OSMC-EV in Beijing, shows that overvoltage fault for Li-ion batteries cell can be observed from the voltage curves. To further locate abnormal cells and predict faults, an entropy weight method is established to calculate the objective weight, which reduces the subjectivity and improves the reliability. The result clearly identifies the abnormity of cell voltage. The proposed diagnostic model can be used for EV real-time diagnosis without laboratory testing methods. It is more effective than traditional methods based on contrastive analysis.

Renewable-Biomolecule-Based Full Lithium-Ion Batteries.

Science.gov (United States)

Hu, Pengfei; Wang, Hua; Yang, Yun; Yang, Jie; Lin, Jie; Guo, Lin

2016-05-01

A renewable-biomolecule-based full lithium-ion battery is successfully fabricated for the first time. Naturally derivable emodin and humic acid based electrodes are used as cathode and anode, respectively. The as-assembled batteries exhibit superb specific capacity and substantial operating voltage capable of powering a wearable electronic watch, suggesting the great potential for practical applications with the significant merits of sustainability and biocompatibility. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Energy-saving management modelling and optimization for lead-acid battery formation process

Science.gov (United States)

Wang, T.; Chen, Z.; Xu, J. Y.; Wang, F. Y.; Liu, H. M.

2017-11-01

In this context, a typical lead-acid battery producing process is introduced. Based on the formation process, an efficiency management method is proposed. An optimization model with the objective to minimize the formation electricity cost in a single period is established. This optimization model considers several related constraints, together with two influencing factors including the transformation efficiency of IGBT charge-and-discharge machine and the time-of-use price. An example simulation is shown using PSO algorithm to solve this mathematic model, and the proposed optimization strategy is proved to be effective and learnable for energy-saving and efficiency optimization in battery producing industries.

Rechargeable Aluminum-Ion Batteries Based on an Open-Tunnel Framework.

Science.gov (United States)

Kaveevivitchai, Watchareeya; Huq, Ashfia; Wang, Shaofei; Park, Min Je; Manthiram, Arumugam

2017-09-01

Rechargeable batteries based on an abundant metal such as aluminum with a three-electron transfer per atom are promising for large-scale electrochemical energy storage. Aluminum can be handled in air, thus offering superior safety, easy fabrication, and low cost. However, the development of Al-ion batteries has been challenging due to the difficulties in identifying suitable cathode materials. This study presents the use of a highly open framework Mo 2.5 +  y VO 9 +  z as a cathode for Al-ion batteries. The open-tunnel oxide allows a facile diffusion of the guest species and provides sufficient redox centers to help redistribute the charge within the local host lattice during the multivalent-ion insertion, thus leading to good rate capability with a specific capacity among the highest reported in the literature for Al-based batteries. This study also presents the use of Mo 2.5 +  y VO 9 +  z as a model host to develop a novel ultrafast technique for chemical insertion of Al ions into host structures. The microwave-assisted method employing diethylene glycol and aluminum diacetate (Al(OH)(C 2 H 3 O 2 ) 2 ) can be performed in air in as little as 30 min, which is far superior to the traditional chemical insertion techniques involving moisture-sensitive organometallic reagents. The Al-inserted Al x Mo 2.5 +  y VO 9 +  z obtained by the microwave-assisted chemical insertion can be used in Al-based rechargeable batteries. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A mathematical model for the iron/chromium redox battery

Science.gov (United States)

Fedkiw, P. S.; Watts, R. W.

1984-01-01

A mathematical model has been developed to describe the isothermal operation of a single anode-separator-cathode unit cell in a redox-flow battery and has been applied to the NASA iron/chromium system. The model, based on porous electrode theory, incorporates redox kinetics, mass transfer, and ohmic effects as well as the parasitic hydrogen reaction which occurs in the chromium electrode. A numerical parameter study was carried out to predict cell performance to aid in the rational design, scale-up, and operation of the flow battery. The calculations demonstrate: (1) an optimum electrode thickness and electrolyte flow rate exist; (2) the amount of hydrogen evolved and, hence, cycle faradaic efficiency, can be affected by cell geometry, flow rate, and charging procedure; (3) countercurrent flow results in enhanced cell performance over cocurrent flow; and (4) elevated temperature operation enhances cell performance.

On-line adaptive battery impedance parameter and state estimation considering physical principles in reduced order equivalent circuit battery models part 2. Parameter and state estimation

Science.gov (United States)

Fleischer, Christian; Waag, Wladislaw; Heyn, Hans-Martin; Sauer, Dirk Uwe

2014-09-01

Lithium-ion battery systems employed in high power demanding systems such as electric vehicles require a sophisticated monitoring system to ensure safe and reliable operation. Three major states of the battery are of special interest and need to be constantly monitored. These include: battery state of charge (SoC), battery state of health (capacity fade determination, SoH), and state of function (power fade determination, SoF). The second paper concludes the series by presenting a multi-stage online parameter identification technique based on a weighted recursive least quadratic squares parameter estimator to determine the parameters of the proposed battery model from the first paper during operation. A novel mutation based algorithm is developed to determine the nonlinear current dependency of the charge-transfer resistance. The influence of diffusion is determined by an on-line identification technique and verified on several batteries at different operation conditions. This method guarantees a short response time and, together with its fully recursive structure, assures a long-term stable monitoring of the battery parameters. The relative dynamic voltage prediction error of the algorithm is reduced to 2%. The changes of parameters are used to determine the states of the battery. The algorithm is real-time capable and can be implemented on embedded systems.

Peukert-Equation-Based State-of-Charge Estimation for LiFePO4 Batteries Considering the Battery Thermal Evolution Effect

Directory of Open Access Journals (Sweden)

Jiale Xie

2018-05-01

Full Text Available To achieve accurate state-of-charge (SoC estimation for LiFePO4 (lithium iron phosphate batteries under harsh conditions, this paper resorts to the Peukert’s law to accommodate different temperatures and load excitations. By analyzing battery heat generation and dissipation, a thermal evolution model (TEM is elaborated and exploited for on-line parameter identification of the equivalent circuit model (ECM. Then, a SoC estimation framework is proposed based on the Adaptive Extended Kalman Filter (AEKF algorithm. Experimental results on a LiFePO4 pack subject to the Federal Urban Driving Schedule (FUDS profile under different temperatures and initial states suggest that the proposed SoC estimator provides good robustness and accuracy against changing temperature and highly dynamic loads.

Graphene-Based Composites as Cathode Materials for Lithium Ion Batteries

Directory of Open Access Journals (Sweden)

Libao Chen

2013-01-01

Full Text Available Owing to the superior mechanical, thermal, and electrical properties, graphene was a perfect candidate to improve the performance of lithium ion batteries. Herein, we review the recent advances in graphene-based composites and their application as cathode materials for lithium ion batteries. We focus on the synthesis methods of graphene-based composites and the superior electrochemical performance of graphene-based composites as cathode materials for lithium ion batteries.

Simulation of hybrid vehicle propulsion with an advanced battery model

Energy Technology Data Exchange (ETDEWEB)

Nallabolu, S.; Kostetzer, L.; Rudnyi, E. [CADFEM GmbH, Grafing (Germany); Geppert, M.; Quinger, D. [LION Smart GmbH, Frieding (Germany)

2011-07-01

In the recent years there has been observed an increasing concern about global warming and greenhouse gas emissions. In addition to the environmental issues the predicted scarcity of oil supplies and the dramatic increase in oil price puts new demands on vehicle design. As a result energy efficiency and reduced emission have become one of main selling point for automobiles. Hybrid electric vehicles (HEV) have therefore become an interesting technology for the governments and automotive industries. HEV are more complicated compared to conventional vehicles due to the fact that these vehicles contain more electrical components such as electric machines, power electronics, electronic continuously variable transmissions (CVT), and embedded powertrain controllers. Advanced energy storage devices and energy converters, such as Li-ion batteries, ultracapacitors, and fuel cells are also considered. A detailed vehicle model used for an energy flow analysis and vehicle performance simulation is necessary. Computer simulation is indispensible to facilitate the examination of the vast hybrid electric vehicle design space with the aim to predict the vehicle performance over driving profiles, estimate fuel consumption and the pollution emissions. There are various types of mathematical models and simulators available to perform system simulation of vehicle propulsion. One of the standard methods to model the complete vehicle powertrain is ''backward quasistatic modeling''. In this method vehicle subsystems are defined based on experiential models in the form of look-up tables and efficiency maps. The interaction between adjacent subsystems of the vehicle is defined through the amount of power flow. Modeling the vehicle subsystems like motor, engine, gearbox and battery is under this technique is based on block diagrams. The vehicle model is applied in two case studies to evaluate the vehicle performance and fuel consumption. In the first case study the affect

Investigation on a hydrogel based passive thermal management system for lithium ion batteries

International Nuclear Information System (INIS)

Zhang, Sijie; Zhao, Rui; Liu, Jie; Gu, Junjie

2014-01-01

An appropriate operating temperature range is critical for the overall performance and safety of lithium-ion batteries. Considering the excellent performance of water in heat dissipation in industrial applications, in this paper, a water based PAAS (sodium polyacrylate) hydrogel thermal management system has been proposed to handle the heat surge during the operation of a Li-ion battery pack. A thermal model with constant heat generation rate is employed to simulate the high current discharge process (i.e., 10 A) on a 4S1P battery pack, which shows a good consistence with the corresponding experimental results. Further experiments on 4S1P and 5S1P battery packs validate the effectiveness of the hydrogel thermal management system in lowering the temperature increase rate of battery packs at different discharge rates and minimizing the temperature difference inside battery packs during operation, thereby enhancing the stability and safety in continuous charge and discharge process and decreasing the capacity fading rate during life cycle tests. This novel hydrogel based cooling system also possesses the characteristics of high energy efficiency, easy manufacturing process, compactness, and low cost. - Highlights: • A hydrogel thermal management system (TMS) is proposed for Li-ion battery. • It is found that the heat from internal resistance predominates at high discharge rate. • Effectiveness of hydrogel in controlling cell temperature is proved. • Battery equipped with hydrogel TMS is safer at continuous high rate cycle test. • The capacity fading rate of battery pack decreases when hydrogel TMS is implemented

Homogenized modeling methodology for 18650 lithium-ion battery module under large deformation

Science.gov (United States)

Tang, Liang; Cheng, Pengle

2017-01-01

Effective lithium-ion battery module modeling has become a bottleneck for full-size electric vehicle crash safety numerical simulation. Modeling every single cell in detail would be costly. However, computational accuracy could be lost if the module is modeled by using a simple bulk material or rigid body. To solve this critical engineering problem, a general method to establish a computational homogenized model for the cylindrical battery module is proposed. A single battery cell model is developed and validated through radial compression and bending experiments. To analyze the homogenized mechanical properties of the module, a representative unit cell (RUC) is extracted with the periodic boundary condition applied on it. An elastic–plastic constitutive model is established to describe the computational homogenized model for the module. Two typical packing modes, i.e., cubic dense packing and hexagonal packing for the homogenized equivalent battery module (EBM) model, are targeted for validation compression tests, as well as the models with detailed single cell description. Further, the homogenized EBM model is confirmed to agree reasonably well with the detailed battery module (DBM) model for different packing modes with a length scale of up to 15 × 15 cells and 12% deformation where the short circuit takes place. The suggested homogenized model for battery module makes way for battery module and pack safety evaluation for full-size electric vehicle crashworthiness analysis. PMID:28746390

Homogenized modeling methodology for 18650 lithium-ion battery module under large deformation.

Directory of Open Access Journals (Sweden)

Liang Tang

Full Text Available Effective lithium-ion battery module modeling has become a bottleneck for full-size electric vehicle crash safety numerical simulation. Modeling every single cell in detail would be costly. However, computational accuracy could be lost if the module is modeled by using a simple bulk material or rigid body. To solve this critical engineering problem, a general method to establish a computational homogenized model for the cylindrical battery module is proposed. A single battery cell model is developed and validated through radial compression and bending experiments. To analyze the homogenized mechanical properties of the module, a representative unit cell (RUC is extracted with the periodic boundary condition applied on it. An elastic-plastic constitutive model is established to describe the computational homogenized model for the module. Two typical packing modes, i.e., cubic dense packing and hexagonal packing for the homogenized equivalent battery module (EBM model, are targeted for validation compression tests, as well as the models with detailed single cell description. Further, the homogenized EBM model is confirmed to agree reasonably well with the detailed battery module (DBM model for different packing modes with a length scale of up to 15 × 15 cells and 12% deformation where the short circuit takes place. The suggested homogenized model for battery module makes way for battery module and pack safety evaluation for full-size electric vehicle crashworthiness analysis.

Dynamical modeling procedure of a Li-ion battery pack suitable for real-time applications

International Nuclear Information System (INIS)

Castano, S.; Gauchia, L.; Voncila, E.; Sanz, J.

2015-01-01

Highlights: • Dynamical modeling of a 50 A h battery pack composed of 56 cells. • Detailed analysis of SOC tests at realistic performance range imposed by BMS. • We propose an electrical circuit that improves how the battery capacity is modeled. • The model is validated in the SOC range using a real-time experimental setup. - Abstract: This paper presents the modeling of a 50 A h battery pack composed of 56 cells, taking into account real battery performance conditions imposed by the BMS control. The modeling procedure starts with a detailed analysis of experimental charge and discharge SOC tests. Results from these tests are used to obtain the battery model parameters at a realistic performance range (20–80% SOC). The model topology aims to better describe the finite charge contained in a battery pack. The model has been validated at three different SOC values in order to verify the model response at real battery pack operation conditions. The validation tests show that the battery pack model is able to simulate the real battery response with excellent accuracy in the range tested. The proposed modeling procedure is fully applicable to any Li-ion battery pack, regardless of the number of series or parallel cells or its rated capacity

Supercapacitor performance evaluation in replacing battery based on charging and discharging current characteristics

Science.gov (United States)

Sani, A.; Siahaan, S.; Mubarakah, N.; Suherman

2018-02-01

Supercapacitor is a new device of energy storage, which has much difference between ordinary capacitors and batteries. Supercapacitor have higher capacitance and energy density than regular capacitors. The supercapacitor also has a fast charging time, as well as a long life. To be used as a battery replacement please note the internal parameters of the battery to be replaced. In this paper conducted a simulation study to utilize supercapacitor as a replacement battery. The internal parameters of the battery and the supercapacitor are obtained based on the characteristics of charging and discharging current using a predefined equivalent circuit model. The battery to be replaced is a 12-volt lead-acid type, 6.5 Ah which is used on motorcycles with 6A charging and discharging currents. Super capacitor replacement capacitor is a capacity of 1600F, 2.7V which is connected in series as many as 6 pieces with 16.2 volt terminal voltage and charging current 12A. To obtain the same supercapacitor characteristic as the battery characteristic to be replaced, modification of its internal parameters is made. The results show that the super-capacitor can replace the battery function for 1000 seconds.

A control-oriented cycle-life model for hybrid electric vehicle lithium-ion batteries

International Nuclear Information System (INIS)

Suri, Girish; Onori, Simona

2016-01-01

In this paper, a semi-empirical Lithium-iron phosphate-graphite battery aging model is identified over data mimicking actual cycling conditions that a hybrid electric vehicle battery encounters under real driving scenarios. The aging model is then used to construct the severity factor map, used to characterize relative aging of the battery under different operating conditions. This is used as a battery degradation criterion within a multi-objective optimization problem where battery aging minimization is to be achieved along with fuel consumption minimization. The method proposed is general and can be applied to other battery chemistry as well as different vehicular applications. Finally, simulations conducted using a hybrid electric vehicle simulator show how the two modeling tools developed in this paper, i.e., the severity factor map and the aging model, can be effectively used in a multi-objective optimization problem to predict and control battery degradation. - Highlights: • Battery aging model for hybrid electric vehicles using real driving conditions data. • Development of a modeling tool to assess battery degradation for real time optimization. • "3"1P NMR analysis of an enzyme-treated extract showed expected hydrolysis of P forms. • Development of an energy management strategy to minimize battery degradation. • Simulation results from hybrid electric vehicle simulator.

An on-line estimation of battery pack parameters and state-of-charge using dual filters based on pack model

International Nuclear Information System (INIS)

Zhang, Xu; Wang, Yujie; Yang, Duo; Chen, Zonghai

2016-01-01

Accurate estimation of battery pack state-of-charge plays a very important role for electric vehicles, which directly reflects the behavior of battery pack usage. However, the inconsistency of battery makes the estimation of battery pack state-of-charge different from single cell. In this paper, to estimate the battery pack state-of-charge on-line, the definition of battery pack is proposed, and the relationship between the total available capacity of battery pack and single cell is put forward to analyze the energy efficiency influenced by battery inconsistency, then a lumped parameter battery model is built up to describe the dynamic behavior of battery pack. Furthermore, the extend Kalman filter-unscented Kalman filter algorithm is developed to identify the parameters of battery pack and forecast state-of-charge concurrently. The extend Kalman filter is applied to update the battery pack parameters by real-time measured data, while the unscented Kalman filter is employed to estimate the battery pack state-of-charge. Finally, the proposed approach is verified by experiments operated on the lithium-ion battery under constant current condition and the dynamic stress test profiles. Experimental results indicate that the proposed method can estimate the battery pack state-of-charge with high accuracy. - Highlights: • A novel space state equation is built to describe the pack dynamic behavior. • The dual filters method is used to estimate the pack state-of-charge. • Battery inconsistency is considered to analyze the pack usage efficiency. • The accuracy of the proposed method is verified under different conditions.

Power capability prediction for lithium-ion batteries based on multiple constraints analysis

International Nuclear Information System (INIS)

Pan, Rui; Wang, Yujie; Zhang, Xu; Yang, Duo; Chen, Zonghai

2017-01-01

Highlights: • Multiple constraints for peak power capability prediction are deeply analyzed. • Multi-limited method is proposed for the peak power capability prediction of LIBs. • The EKF is used for the model based peak power capability prediction. • The FUDS and UDDS profiles are executed to evaluate the proposed method. - Abstract: The power capability of the lithium-ion battery is a key performance indicator for electric vehicle, and it is intimately correlated with the acceleration, regenerative braking and gradient climbing power requirements. Therefore, an accurate power capability or state-of-power prediction is critical to a battery management system, which can help the battery to work in suitable area and prevent the battery from over-charging and over-discharging. However, the power capability is easily affected by dynamic load, voltage variation and temperature. In this paper, three different constraints in power capability prediction are introduced, and the advantages and disadvantages of the three methods are deeply analyzed. Furthermore, a multi-limited approach for the power capability prediction is proposed, which can overcome the drawbacks of the three methods. Subsequently, the extended Kalman filter algorithm is employed for model based state-of-power prediction. In order to verify the proposed method, diverse experiments are executed to explore the efficiency, robustness, and precision. The results indicate that the proposed method can improve the precision and robustness obviously.

Thermal modeling of cylindrical lithium ion battery during discharge cycle

International Nuclear Information System (INIS)

Jeon, Dong Hyup; Baek, Seung Man

2011-01-01

Highlights: → Transient and thermo-electric finite element analysis (FEA) of cylindrical lithium ion (Li-ion) battery was presented. → This model provides the thermal behavior of Li-ion battery during discharge cycle. → A LiCoO 2 /C battery at various discharge rates was investigated. → The contribution of heat source due to joule heating was significant at a high discharge rate. → The contribution of heat source due to entropy change was dominant at a low discharge rate. - Abstract: Transient and thermo-electric finite element analysis (FEA) of cylindrical lithium ion (Li-ion) battery was presented. The simplified model by adopting a cylindrical coordinate was employed. This model provides the thermal behavior of Li-ion battery during discharge cycle. The mathematical model solves conservation of energy considering heat generations due to both joule heating and entropy change. A LiCoO 2 /C battery at various discharge rates was investigated. The temperature profile from simulation had similar tendency with experiment. The temperature profile was decomposed with contributions of each heat sources and was presented at several discharge rates. It was found that the contribution of heat source due to joule heating was significant at a high discharge rate, whereas that due to entropy change was dominant at a low discharge rate. Also the effect of cooling condition and the LiNiCoMnO 2 /C battery were analyzed for the purpose of temperature reduction.

A low cost, microprocessor-based battery charge controller

Energy Technology Data Exchange (ETDEWEB)

Pulfrey, D L; Hacker, J [Pulfrey Solar Inc., Vancouver, BC (Canada)

1990-01-01

This report describes the design, construction, testing, and evaluation of a microprocessor-based battery charge controller that uses charge integration as the method of battery state-of-charge estimation. The controller is intended for use in medium-size (100-1000W) photovoltaic systems that employ 12V lead-acid batteries for charge storage. The controller regulates the charge flow to the battery and operates in three, automatically-determined modes, namely: charge, equalize, and float. The prototype controller is modular in nature and can handle charge/discharge currents of magnitude up to 80A, depending on the number of circuit boards employed. Evaluation tests and field trials have shown the controller to be very accurate and reliable. Based on the cost of the prototype, it appears that an original equipment manufacturer's selling price of $400 for a 40A (500W) unit may be realistic. 18 figs., 2 tabs.

Economic models for battery energy storage

International Nuclear Information System (INIS)

Reckrodt, R.C.; Anderson, M.D.; Kluczny, R.M.

1990-01-01

While the technology required to produce viable Battery Energy Storage System exists, the economic feasibility (cost vs. benefits) of building these systems requires justification. First, a generalized decision diagram was developed to ensure that all of the economic factors were considered and properly related for the customer-side-of-the meter. Next, two economic models that had consistently given differing results were compared. One was the McKinney model developed at UM-Rolla in 1987; the second was the SYSPLAN model developed by Battelle. Differences were resolved on a point by point basis with reference to the current economic environment. The economic model was upgraded to include the best of both models based on the resolution of these differences. The upgrades were implemented as modifications to the original SYSPLAN (1986 version) to preserve user friendliness. In this paper four specific cases are evaluated and compared. The results are as predicted, since comparison was made with two known models

A 3D thermal runaway propagation model for a large format lithium ion battery module

International Nuclear Information System (INIS)

Feng, Xuning; Lu, Languang; Ouyang, Minggao; Li, Jiangqiu; He, Xiangming

2016-01-01

In this paper, a 3D thermal runaway (TR) propagation model is built for a large format lithium ion battery module. The 3D TR propagation model is built based on the energy balance equation. Empirical equations are utilized to simplify the calculation of the chemical kinetics for TR, whereas equivalent thermal resistant layer is employed to simplify the heat transfer through the thin thermal layer. The 3D TR propagation model is validated by experiment and can provide beneficial discussions on the mechanisms of TR propagation. According to the modeling analysis of the 3D model, the TR propagation can be delayed or prevented through: 1) increasing the TR triggering temperature; 2) reducing the total electric energy released during TR; 3) enhancing the heat dissipation level; 4) adding extra thermal resistant layer between adjacent batteries. The TR propagation is successfully prevented in the model and validated by experiment. The model with 3D temperature distribution provides a beneficial tool for researchers to study the TR propagation mechanisms and for engineers to design a safer battery pack. - Highlights: • A 3D thermal runaway (TR) propagation model for Li-ion battery pack is built. • The 3D TR propagation model can fit experimental results well. • Temperature distributions during TR propagation are presented using the 3D model. • Modeling analysis provides solutions for the prevention of TR propagation. • Quantified solutions to prevent TR propagation in battery pack are discussed.

Correlation between the model accuracy and model-based SOC estimation

International Nuclear Information System (INIS)

Wang, Qianqian; Wang, Jiao; Zhao, Pengju; Kang, Jianqiang; Yan, Few; Du, Changqing

2017-01-01

State-of-charge (SOC) estimation is a core technology for battery management systems. Considerable progress has been achieved in the study of SOC estimation algorithms, especially the algorithm on the basis of Kalman filter to meet the increasing demand of model-based battery management systems. The Kalman filter weakens the influence of white noise and initial error during SOC estimation but cannot eliminate the existing error of the battery model itself. As such, the accuracy of SOC estimation is directly related to the accuracy of the battery model. Thus far, the quantitative relationship between model accuracy and model-based SOC estimation remains unknown. This study summarizes three equivalent circuit lithium-ion battery models, namely, Thevenin, PNGV, and DP models. The model parameters are identified through hybrid pulse power characterization test. The three models are evaluated, and SOC estimation conducted by EKF-Ah method under three operating conditions are quantitatively studied. The regression and correlation of the standard deviation and normalized RMSE are studied and compared between the model error and the SOC estimation error. These parameters exhibit a strong linear relationship. Results indicate that the model accuracy affects the SOC estimation accuracy mainly in two ways: dispersion of the frequency distribution of the error and the overall level of the error. On the basis of the relationship between model error and SOC estimation error, our study provides a strategy for selecting a suitable cell model to meet the requirements of SOC precision using Kalman filter.

Battery Aging and the Kinetic Battery Model

NARCIS (Netherlands)

Jongerden, M.R.; Haverkort, Boudewijn R.H.M.

2016-01-01

Batteries are omnipresent, and with the uprise of the electrical vehicles will their use will grow even more. However, the batteries can deliver their required power for a limited time span. They slowly degrade with every charge-discharge cycle. This degradation needs to be taken into account when

A flexible model for economic operational management of grid battery energy storage

International Nuclear Information System (INIS)

Fares, Robert L.; Webber, Michael E.

2014-01-01

To connect energy storage operational planning with real-time battery control, this paper integrates a dynamic battery model with an optimization program. First, we transform a behavioral circuit model designed to describe a variety of battery chemistries into a set of coupled nonlinear differential equations. Then, we discretize the differential equations to integrate the battery model with a GAMS (General Algebraic Modeling System) optimization program, which decides when the battery should charge and discharge to maximize its operating revenue. We demonstrate the capabilities of our model by applying it to lithium-ion (Li-ion) energy storage operating in Texas' restructured electricity market. By simulating 11 years of operation, we find that our model can robustly compute an optimal charge-discharge schedule that maximizes daily operating revenue without violating a battery's operating constraints. Furthermore, our results show there is significant variation in potential operating revenue from one day to the next. The revenue potential of Li-ion storage varies from approximately $0–1800/MWh of energy discharged, depending on the volatility of wholesale electricity prices during an operating day. Thus, it is important to consider the material degradation-related “cost” of performing a charge-discharge cycle in battery operational management, so that the battery only operates when revenue exceeds cost. - Highlights: • A flexible, dynamic battery model is integrated with an optimization program. • Electricity price data is used to simulate 11 years of Li-ion operation on the grid. • The optimization program robustly computes an optimal charge-discharge schedule. • Variation in daily Li-ion battery revenue potential from 2002 to 2012 is shown. • We find it is important to consider the cost of a grid duty cycle

A Thermal Runaway Simulation on a Lithium Titanate Battery and the Battery Module

Directory of Open Access Journals (Sweden)

Man Chen

2015-01-01

Full Text Available Based on the electrochemical and thermal model, a coupled electro-thermal runaway model was developed and implemented using finite element methods. The thermal decomposition reactions when the battery temperature exceeds the material decomposition temperature were embedded into the model. The temperature variations of a lithium titanate battery during a series of charge-discharge cycles under different current rates were simulated. The results of temperature and heat generation rate demonstrate that the greater the current, the faster the battery temperature is rising. Furthermore, the thermal influence of the overheated cell on surrounding batteries in the module was simulated, and the variation of temperature and heat generation during thermal runaway was obtained. It was found that the overheated cell can induce thermal runaway in other adjacent cells within 3 mm distance in the battery module if the accumulated heat is not dissipated rapidly.

Online Internal Temperature Estimation for Lithium-Ion Batteries Based on Kalman Filter

Directory of Open Access Journals (Sweden)

Jinlei Sun

2015-05-01

Full Text Available The battery internal temperature estimation is important for the thermal safety in applications, because the internal temperature is hard to measure directly. In this work, an online internal temperature estimation method based on a simplified thermal model using a Kalman filter is proposed. As an improvement, the influences of entropy change and overpotential on heat generation are analyzed quantitatively. The model parameters are identified through a current pulse test. The charge/discharge experiments under different current rates are carried out on the same battery to verify the estimation results. The internal and surface temperatures are measured with thermocouples for result validation and model construction. The accuracy of the estimated result is validated with a maximum estimation error of around 1 K.

Development of single cell lithium ion battery model using Scilab/Xcos

Science.gov (United States)

Arianto, Sigit; Yunaningsih, Rietje Y.; Astuti, Edi Tri; Hafiz, Samsul

2016-02-01

In this research, a lithium battery model, as a component in a simulation environment, was developed and implemented using Scicos/Xcos graphical language programming. Scicos used in this research was actually Xcos that is a variant of Scicos which is embedded in Scilab. The equivalent circuit model used in modeling the battery was Double Polarization (DP) model. DP model consists of one open circuit voltage (VOC), one internal resistance (Ri), and two parallel RC circuits. The parameters of the battery were extracted using Hybrid Power Pulse Characterization (HPPC) testing. In this experiment, the Double Polarization (DP) electrical circuit model was used to describe the lithium battery dynamic behavior. The results of simulation of the model were validated with the experimental results. Using simple error analysis, it was found out that the biggest error was 0.275 Volt. It was occurred mostly at the low end of the state of charge (SOC).

In-situ Fabrication of a Freestanding Acrylate-based Hierarchical Electrolyte for Lithium-sulfur Batteries

International Nuclear Information System (INIS)

Liu, M.; Jiang, H.R.; Ren, Y.X.; Zhou, D.; Kang, F.Y.; Zhao, T.S.

2016-01-01

Graphical abstract: We present a freestanding acrylate-based hierarchical electrolyte. This quasi-solid electrolyte is assembled by in-situ gelation of a pentaerythritol tetraacrylate (PETEA)-based gel polymer electrolyte (GPE) into a polymethyl methacrylate (PMMA)-based electrospun network. The prepared polymer battery renders a suppressed shuttle effect and much enhanced cycle life. - Highlights: • A freestanding Acrylate-based Hierarchical Electrolyte was in-situ crafted. • The high conductivity is due to strong uptake ability and elimination of separator. • The polymer battery renders a superior high rate capability and excellent retention. • First-principle calculations prove anchoring ability of ester functional groups. • Cell modeling shows geometric design effectively suppresses polysulfide flux. - Abstract: A number of methods have been attempted to suppress the shuttle effect in lithium-sulfur (Li-S) batteries to improve battery performance. Conventional methods, however, reduce the ionic conductivity, sacrifice the overall energy density and increase the cost of production. Here, we report a facile synthesis of an acrylate-based hierarchical electrolyte (AHE). This quasi-solid electrolyte is assembled by in-situ gelation of a pentaerythritol tetraacrylate (PETEA)-based gel polymer electrolyte (GPE) into a polymethyl methacrylate (PMMA)-based electrospun network. The structural similarity and synergetic compatibility between the electrospun network and GPE provide the AHE an ester-rich robust structure with a high ionic conductivity of 1.02 × 10 −3 S cm −1 due to the strong uptake ability and the elimination of commercial separator. The S/AHE/Li polymer battery also renders a high rate capability of 645 mAh g −1 at 3C, while maintaining excellent retention at both high and low current densities (80.3% after 500 cycles at 0.3C and 91.9% after 500 cycles at 3C). First-principle calculations reveal that the reduced shuttle effect can be

A Novel Method for Lithium-Ion Battery Online Parameter Identification Based on Variable Forgetting Factor Recursive Least Squares

Directory of Open Access Journals (Sweden)

Zizhou Lao

2018-05-01

Full Text Available For model-based state of charge (SOC estimation methods, the battery model parameters change with temperature, SOC, and so forth, causing the estimation error to increase. Constantly updating model parameters during battery operation, also known as online parameter identification, can effectively solve this problem. In this paper, a lithium-ion battery is modeled using the Thevenin model. A variable forgetting factor (VFF strategy is introduced to improve forgetting factor recursive least squares (FFRLS to variable forgetting factor recursive least squares (VFF-RLS. A novel method based on VFF-RLS for the online identification of the Thevenin model is proposed. Experiments verified that VFF-RLS gives more stable online parameter identification results than FFRLS. Combined with an unscented Kalman filter (UKF algorithm, a joint algorithm named VFF-RLS-UKF is proposed for SOC estimation. In a variable-temperature environment, a battery SOC estimation experiment was performed using the joint algorithm. The average error of the SOC estimation was as low as 0.595% in some experiments. Experiments showed that VFF-RLS can effectively track the changes in model parameters. The joint algorithm improved the SOC estimation accuracy compared to the method with the fixed forgetting factor.

Modeling the Effects of the Cathode Composition of a Lithium Iron Phosphate Battery on the Discharge Behavior

Directory of Open Access Journals (Sweden)

Won Il Cho

2013-10-01

Full Text Available This paper reports a modeling methodology to predict the effects on the discharge behavior of the cathode composition of a lithium iron phosphate (LFP battery cell comprising a LFP cathode, a lithium metal anode, and an organic electrolyte. A one-dimensional model based on a finite element method is presented to calculate the cell voltage change of a LFP battery cell during galvanostatic discharge. To test the validity of the modeling approach, the modeling results for the variations of the cell voltage of the LFP battery as a function of time are compared with the experimental measurements during galvanostatic discharge at various discharge rates of 0.1C, 0.5C, 1.0C, and 2.0C for three different compositions of the LFP cathode. The discharge curves obtained from the model are in good agreement with the experimental measurements. On the basis of the validated modeling approach, the effects of the cathode composition on the discharge behavior of a LFP battery cell are estimated. The modeling results exhibit highly nonlinear dependencies of the discharge behavior of a LFP battery cell on the discharge C-rate and cathode composition.

Lead/acid batteries for photovoltaic applications. Test results and modelling

Energy Technology Data Exchange (ETDEWEB)

Copetti, J B [CIEMAT, Inst. de Energias Renovables, Madrid (Spain); Chenlo, F [CIEMAT, Inst. de Energias Renovables, Madrid (Spain)

1994-01-01

This work presents the results of experiments carried out on lead/acid batteries during charge and discharge processes at different currents and temperatures, selected to a cover a large range of operating conditions, including those encountered in photovoltaic (PV) system applications. The results allow us to verify the relations among the battery external parameters (voltage, current, state-of-charge and temperature), the behaviour of the internal resistance, and to deduce a model that represents the discharge and charge processes, including the overcharge. Finally, normalized equations with respect to the battery capacity are proposed, which allow us to fix the values of parameters and hence the model is valid for any type and size of lead/acid battery. (orig.)

A control-oriented lithium-ion battery pack model for plug-in hybrid electric vehicle cycle-life studies and system design with consideration of health management

Science.gov (United States)

Cordoba-Arenas, Andrea; Onori, Simona; Rizzoni, Giorgio

2015-04-01

A crucial step towards the large-scale introduction of plug-in hybrid electric vehicles (PHEVs) in the market is to reduce the cost of its battery systems. Currently, battery cycle- and calendar-life represents one of the greatest uncertainties in the total life-cycle cost of battery systems. The field of battery aging modeling and prognosis has seen progress with respect to model-based and data-driven approaches to describe the aging of battery cells. However, in real world applications cells are interconnected and aging propagates. The propagation of aging from one cell to others exhibits itself in a reduced battery system life. This paper proposes a control-oriented battery pack model that describes the propagation of aging and its effect on the life span of battery systems. The modeling approach is such that it is able to predict pack aging, thermal, and electrical dynamics under actual PHEV operation, and includes consideration of random variability of the cells, electrical topology and thermal management. The modeling approach is based on the interaction between dynamic system models of the electrical and thermal dynamics, and dynamic models of cell aging. The system-level state-of-health (SOH) is assessed based on knowledge of individual cells SOH, pack electrical topology and voltage equalization approach.

Design And Construction Of Microcontroller Based Solar Battery Charger

Directory of Open Access Journals (Sweden)

Zar Ni Tun

2015-08-01

Full Text Available This research paper describes a microcontroller based battery charger by using solar energy. Solar-powered charging systems are already available in rural as well as urban areas. Solar energy is widely used around the worldwide. This system converts solar energy to electrical energy and stores it in a battery. Photovoltaic panel is used to convert solar energy to electrical energy and stored in a 12V battery. Battery is the main component in solar charging system to store the energy generated from sunlight for various application. This system requires sensor to sense whether the battery is fully charged or not. Microcontroller is the heart of the circuit. Lead-acid batteries are the most commonly used power source for many applications. This system consists of voltage sensing charging controlling and display unit.

Multiscale modeling of lithium ion batteries: thermal aspects

Directory of Open Access Journals (Sweden)

Arnulf Latz

2015-04-01

Full Text Available The thermal behavior of lithium ion batteries has a huge impact on their lifetime and the initiation of degradation processes. The development of hot spots or large local overpotentials leading, e.g., to lithium metal deposition depends on material properties as well as on the nano- und microstructure of the electrodes. In recent years a theoretical structure emerges, which opens the possibility to establish a systematic modeling strategy from atomistic to continuum scale to capture and couple the relevant phenomena on each scale. We outline the building blocks for such a systematic approach and discuss in detail a rigorous approach for the continuum scale based on rational thermodynamics and homogenization theories. Our focus is on the development of a systematic thermodynamically consistent theory for thermal phenomena in batteries at the microstructure scale and at the cell scale. We discuss the importance of carefully defining the continuum fields for being able to compare seemingly different phenomenological theories and for obtaining rules to determine unknown parameters of the theory by experiments or lower-scale theories. The resulting continuum models for the microscopic and the cell scale are numerically solved in full 3D resolution. The complex very localized distributions of heat sources in a microstructure of a battery and the problems of mapping these localized sources on an averaged porous electrode model are discussed by comparing the detailed 3D microstructure-resolved simulations of the heat distribution with the result of the upscaled porous electrode model. It is shown, that not all heat sources that exist on the microstructure scale are represented in the averaged theory due to subtle cancellation effects of interface and bulk heat sources. Nevertheless, we find that in special cases the averaged thermal behavior can be captured very well by porous electrode theory.

Online state of charge and model parameter co-estimation based on a novel multi-timescale estimator for vanadium redox flow battery

International Nuclear Information System (INIS)

Wei, Zhongbao; Lim, Tuti Mariana; Skyllas-Kazacos, Maria; Wai, Nyunt; Tseng, King Jet

2016-01-01

Highlights: • Battery model parameters and SOC co-estimation is investigated. • The model parameters and OCV are decoupled and estimated independently. • Multiple timescales are adopted to improve precision and stability. • SOC is online estimated without using the open-circuit cell. • The method is robust to aging levels, flow rates, and battery chemistries. - Abstract: A key function of battery management system (BMS) is to provide accurate information of the state of charge (SOC) in real time, and this depends directly on the precise model parameterization. In this paper, a novel multi-timescale estimator is proposed to estimate the model parameters and SOC for vanadium redox flow battery (VRB) in real time. The model parameters and OCV are decoupled and estimated independently, effectively avoiding the possibility of cross interference between them. The analysis of model sensitivity, stability, and precision suggests the necessity of adopting different timescales for each estimator independently. Experiments are conducted to assess the performance of the proposed method. Results reveal that the model parameters are online adapted accurately thus the periodical calibration on them can be avoided. The online estimated terminal voltage and SOC are both benchmarked with the reference values. The proposed multi-timescale estimator has the merits of fast convergence, high precision, and good robustness against the initialization uncertainty, aging states, flow rates, and also battery chemistries.

Technical feasibility for commercialization of lithium ion battery as a substitute dry battery for motorcycle

Science.gov (United States)

Kurniyati, Indah; Sutopo, Wahyudi; Zakaria, Roni; Kadir, Evizal Abdul

2017-11-01

Dry battery on a motorcycle has a rapid rate of voltage drop, life time is not too long, and a long charging time. These are problems for users of dry battery for motorcycle. When the rate in the voltage decreases, the energy storage in the battery is reduced, then at the age of one to two years of battery will be dead and cannot be used, it makes the user should replace the battery. New technology development of a motorcycle battery is lithium ion battery. Lithium ion battery has a specification that has been tested and possible to replace dry battery. Characteristics of lithium ion battery can answer the question on the dry battery service life, the rate of decrease in voltage and charging time. This paper discusses about the technical feasibility for commercialization of lithium ion battery for motorcycle battery. Our proposed methodology of technical feasibility by using a goldsmith commercialization model of the technical feasibility and reconfirm the technical standard using the national standard of motorcycle battery. The battery has been through all the stages of the technical feasibility of the goldsmith model. Based on the results of the study, lithium ion batteries have the minimum technical requirements to be commercialized and has been confirmed in accordance with the standard motorcycle battery. This paper results that the lithium ion battery is visible to commercialized by the technical aspect.

Graphene-based integrated electrodes for flexible lithium ion batteries

International Nuclear Information System (INIS)

Shi, Ying; Wen, Lei; Zhou, Guangmin; Chen, Jing; Pei, Songfeng; Huang, Kun; Cheng, Hui-Ming; Li, Feng

2015-01-01

We have prepared flexible free-standing electrodes with anode and cathode active materials deposited on a highly conductive graphene membrane by a two-step filtration method. Compared with conventional electrodes using metal as current collectors, these electrodes have displayed stronger adhesion, superior electrochemical performance, higher energy density, and better flexibility. A full lithium ion battery assembled by adopting these graphene-based electrodes has showed high rate capability and long cyclic life. We have also assembled a thin, lightweight, and flexible lithium ion battery with poly-(dimethyl siloxane) sheets as packaging material to light a red light-emitting diode. This flexible battery can be easily bent without structural failure or performance loss and operated well under a bent state. The fabrication process of these graphene-based integrated electrodes only has two filtration steps; thus it is easy to scale up. These results suggest great potential for these graphene-based flexible batteries in lightweight, bendable, and wearable electronic devices. (paper)

Integrated computation model of lithium-ion battery subject to nail penetration

International Nuclear Information System (INIS)

Liu, Binghe; Yin, Sha; Xu, Jun

2016-01-01

Highlights: • A coupling model to predict battery penetration process is established. • Penetration test is designed and validates the computational model. • Governing factors of the penetration induced short-circuit is discussed. • Critical safety battery design guidance is suggested. - Abstract: The nail penetration of lithium-ion batteries (LIBs) has become a standard battery safety evaluation method to mimic the potential penetration of a foreign object into LIB, which can lead to internal short circuit with catastrophic consequences, such as thermal runaway, fire, and explosion. To provide a safe, time-efficient, and cost-effective method for studying the nail penetration problem, an integrated computational method that considers the mechanical, electrochemical, and thermal behaviors of the jellyroll was developed using a coupled 3D mechanical model, a 1D battery model, and a short circuit model. The integrated model, along with the sub-models, was validated to agree reasonably well with experimental test data. In addition, a comprehensive quantitative analysis of governing factors, e.g., shapes, sizes, and displacements of nails, states of charge, and penetration speeds, was conducted. The proposed computational framework for LIB nail penetration was first introduced. This framework can provide an accurate prediction of the time history profile of battery voltage, temperature, and mechanical behavior. The factors that affected the behavior of the jellyroll under nail penetration were discussed systematically. Results provide a solid foundation for future in-depth studies on LIB nail penetration mechanisms and safety design.

Battery Thermal Characterization

Energy Technology Data Exchange (ETDEWEB)

Keyser, Matthew A [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-08-08

The operating temperature is critical in achieving the right balance between performance, cost, and life for both Li-ion batteries and ultracapacitors. The chemistries of advanced energy-storage devices - such as lithium-based batteries - are very sensitive to operating temperature. High temperatures degrade batteries faster while low temperatures decrease their power and capacity, affecting vehicle range, performance, and cost. Understanding heat generation in battery systems - from the individual cells within a module, to the inter-connects between the cells, and across the entire battery system - is imperative for designing effective thermal-management systems and battery packs. At NREL, we have developed unique capabilities to measure the thermal properties of cells and evaluate thermal performance of battery packs (air or liquid cooled). We also use our electro-thermal finite element models to analyze the thermal performance of battery systems in order to aid battery developers with improved thermal designs. NREL's tools are used to meet the weight, life, cost, and volume goals set by the U.S. Department of Energy for electric drive vehicles.

Progress in electrolytes for rechargeable Li-based batteries and beyond

OpenAIRE

Qi Li; Juner Chen; Lei Fan; Xueqian Kong; Yingying Lu

2016-01-01

Owing to almost unmatched volumetric energy density, Li-based batteries have dominated the portable electronic industry for the past 20 years. Not only will that continue, but they are also now powering plug-in hybrid electric vehicles and zero-emission vehicles. There is impressive progress in the exploration of electrode materials for lithium-based batteries because the electrodes (mainly the cathode) are the limiting factors in terms of overall capacity inside a battery. However, more and ...

Battery parameterisation based on differential evolution via a boundary evolution strategy

DEFF Research Database (Denmark)

Yang, Guangya

2013-01-01

the advances of evolutionary algorithms (EAs). Differential evolution (DE) is selected and modified to parameterise an equivalent circuit model of lithium-ion batteries. A boundary evolution strategy (BES) is developed and incorporated into the DE to update the parameter boundaries during the parameterisation......, as the equivalent circuit model is an abstract map of the battery electric characteristics, the determination of the possible ranges of parameters can be a challenging task. In this paper, an efficient yet easy to implement method is proposed to parameterise the equivalent circuit model of batteries utilising...

Solvation behavior of carbonate-based electrolytes in sodium ion batteries.

Science.gov (United States)

Cresce, Arthur V; Russell, Selena M; Borodin, Oleg; Allen, Joshua A; Schroeder, Marshall A; Dai, Michael; Peng, Jing; Gobet, Mallory P; Greenbaum, Steven G; Rogers, Reginald E; Xu, Kang

2016-12-21

Sodium ion batteries are on the cusp of being a commercially available technology. Compared to lithium ion batteries, sodium ion batteries can potentially offer an attractive dollar-per-kilowatt-hour value, though at the penalty of reduced energy density. As a materials system, sodium ion batteries present a unique opportunity to apply lessons learned in the study of electrolytes for lithium ion batteries; specifically, the behavior of the sodium ion in an organic carbonate solution and the relationship of ion solvation with electrode surface passivation. In this work the Li + and Na + -based solvates were characterized using electrospray mass spectrometry, infrared and Raman spectroscopy, 17 O, 23 Na and pulse field gradient double-stimulated-echo pulse sequence nuclear magnetic resonance (NMR), and conductivity measurements. Spectroscopic evidence demonstrate that the Li + and Na + cations share a number of similar ion-solvent interaction trends, such as a preference in the gas and liquid phase for a solvation shell rich in cyclic carbonates over linear carbonates and fluorinated carbonates. However, quite different IR spectra due to the PF 6 - anion interactions with the Na + and Li + cations were observed and were rationalized with the help of density functional theory (DFT) calculations that were also used to examine the relative free energies of solvates using cluster - continuum models. Ion-solvent distances for Na + were longer than Li + , and Na + had a greater tendency towards forming contact pairs compared to Li + in linear carbonate solvents. In tests of hard carbon Na-ion batteries, performance was not well correlated to Na + solvent preference, leading to the possibility that Na + solvent preference may play a reduced role in the passivation of anode surfaces and overall Na-ion battery performance.

Modeling all-solid-state Li-ion batteries

NARCIS (Netherlands)

Danilov, D.; Niessen, R.A.H.; Notten, P.H.L.

2011-01-01

A mathematical model for all-solid-state Li-ion batteries is presented. The model includes the charge transfer kinetics at the electrode/electrolyte interface, diffusion of lithium in the intercalation electrode, and diffusion and migration of ions in the electrolyte. The model has been applied to

Potassium-Based Dual Ion Battery with Dual-Graphite Electrode.

Science.gov (United States)

Fan, Ling; Liu, Qian; Chen, Suhua; Lin, Kairui; Xu, Zhi; Lu, Bingan

2017-08-01

A potassium ion battery has potential applications for large scale electric energy storage systems due to the abundance and low cost of potassium resources. Dual graphite batteries, with graphite as both anode and cathode, eliminate the use of transition metal compounds and greatly lower the overall cost. Herein, combining the merits of the potassium ion battery and dual graphite battery, a potassium-based dual ion battery with dual-graphite electrode is developed. It delivers a reversible capacity of 62 mA h g -1 and medium discharge voltage of ≈3.96 V. The intercalation/deintercalation mechanism of K + and PF 6 - into/from graphite is proposed and discussed in detail, with various characterizations to support. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Artificial Fish Swarm Algorithm-Based Particle Filter for Li-Ion Battery Life Prediction

Directory of Open Access Journals (Sweden)

Ye Tian

2014-01-01

Full Text Available An intelligent online prognostic approach is proposed for predicting the remaining useful life (RUL of lithium-ion (Li-ion batteries based on artificial fish swarm algorithm (AFSA and particle filter (PF, which is an integrated approach combining model-based method with data-driven method. The parameters, used in the empirical model which is based on the capacity fade trends of Li-ion batteries, are identified dependent on the tracking ability of PF. AFSA-PF aims to improve the performance of the basic PF. By driving the prior particles to the domain with high likelihood, AFSA-PF allows global optimization, prevents particle degeneracy, thereby improving particle distribution and increasing prediction accuracy and algorithm convergence. Data provided by NASA are used to verify this approach and compare it with basic PF and regularized PF. AFSA-PF is shown to be more accurate and precise.

An Online SOC and SOH Estimation Model for Lithium-Ion Batteries

Directory of Open Access Journals (Sweden)

Shyh-Chin Huang

2017-04-01

Full Text Available The monitoring and prognosis of cell degradation in lithium-ion (Li-ion batteries are essential for assuring the reliability and safety of electric and hybrid vehicles. This paper aims to develop a reliable and accurate model for online, simultaneous state-of-charge (SOC and state-of-health (SOH estimations of Li-ion batteries. Through the analysis of battery cycle-life test data, the instantaneous discharging voltage (V and its unit time voltage drop, V′, are proposed as the model parameters for the SOC equation. The SOH equation is found to have a linear relationship with 1/V′ times the modification factor, which is a function of SOC. Four batteries are tested in the laboratory, and the data are regressed for the model coefficients. The results show that the model built upon the data from one single cell is able to estimate the SOC and SOH of the three other cells within a 5% error bound. The derived model is also proven to be robust. A random sampling test to simulate the online real-time SOC and SOH estimation proves that this model is accurate and can be potentially used in an electric vehicle battery management system (BMS.

Non-Intrusive Battery Health Monitoring

Directory of Open Access Journals (Sweden)

Gajewski Laurent

2017-01-01

Full Text Available The “Non-intrusive battery health monitoring”, developed by Airbus Defence and Space (ADS in cooperation with the CIRIMAT-CNRS laboratory and supported by CNES, aims at providing a diagnosis of the battery ageing in flight, called State of Health (SOH, using only the post-treatment of the battery telemetries. The battery current and voltage telemetries are used by a signal processing tool on ground to characterize and to model the battery at low frequencies which allows monitoring the evolution of its degradation with great accuracy. The frequential behaviour estimation is based on inherent disturbances on the current during the nominal functioning of the battery. For instance, on-board thermal control or equipment consumption generates random disturbances on battery current around an average current. The battery voltage response to these current random disturbances enables to model the low frequency impedance of the battery by a signal processing tool. The re-created impedance is then compared with the evolution model of the low frequencies impedance as a function of the battery ageing to estimate accurately battery degradation. Hence, this method could be applied to satellites which are already in orbit and whose battery telemetries acquisition system fulfils the constraints determined in the study. This innovative method is an improvement of present state-of-the-art and is important to have a more accurate in-flight knowledge of battery ageing which is crucial for mission and operation planning and also for possible satellite mission extension or deorbitation. This method is patented by Airbus Defence and Space and CNES.

State of health assessment for lithium batteries based on voltage–time relaxation measure

International Nuclear Information System (INIS)

Baghdadi, Issam; Briat, Olivier; Gyan, Philippe; Vinassa, Jean Michel

2016-01-01

Highlights: • Calendar aging under different storage conditions for three different battery technologies studied. • Two scenarios of aging under power cycling at two different temperatures investigated for one battery technology. • Relaxation profile of battery voltage just after full charge is highly correlated to aging. • Linear dependence between just after charge open circuit voltage and remaining capacity demonstrated. • No computational method and direct prediction of battery state of health or remaining capacity. - Abstract: The performance of lithium batteries degrades over time. The degradation rate strongly depends on stress conditions during use and even at rest. Thus, accurate and rapid diagnosis of battery state of health (SOH) is necessary for electric vehicle manufacturers to manage their vehicle fleets and warranties. This paper demonstrates a simple method for assessing SOH related to battery energy capability (SOH E ). The presented method is based on the monitoring of U relax over aging. U relax is the open-circuit voltage of the battery measured after full charging and 30 min of rest. A linear dependence between U relax and remaining capacity is noted. This correlation is demonstrated for three different commercial battery technologies (different chemistries) aged under different calendar and power cycling aging conditions. It was determined that the difference between two U relax voltages measured at two different aging states is proportional to SOH E decay. The mean error of the linear model is less than 2% for certain cases. This method could also be a highly useful and rapid tool for a complete battery pack diagnosis.

A biomimetic redox flow battery based on flavin mononucleotide.

Science.gov (United States)

Orita, Akihiro; Verde, Michael G; Sakai, Masanori; Meng, Ying Shirley

2016-10-21

The versatility in design of redox flow batteries makes them apt to efficiently store energy in large-scale applications at low cost. The discovery of inexpensive organic electroactive materials for use in aqueous flow battery electrolytes is highly attractive, but is thus far limited. Here we report on a flow battery using an aqueous electrolyte based on the sodium salt of flavin mononucleotide. Flavins are highly versatile electroactive molecules, which catalyse a multitude of redox reactions in biological systems. We use nicotinamide (vitamin B3) as a hydrotropic agent to enhance the water solubility of flavin mononucleotide. A redox flow battery using flavin mononucleotide negative and ferrocyanide positive electrolytes in strong base shows stable cycling performance, with over 99% capacity retention over the course of 100 cycles. We hypothesize that this is enabled due to the oxidized and reduced forms of FMN-Na being stabilized by resonance structures.

Betavoltaic Battery Conversion Efficiency Improvement Based on Interlayer Structures

International Nuclear Information System (INIS)

Li Da-Rang; Jiang Lan; Yin Jian-Hua; Lin Nai; Tan Yuan-Yuan

2012-01-01

Significant differences among the doping densities of PN junctions in semiconductors cause lattice mismatch and lattice defects that increase the recombination current of betavoltaic batteries. This extensively decreases the open circuit voltage and the short current, which results in low conversion efficiency. This study proposes P + PINN + -structure based betavoltaic batteries by adding an interlayer to typical PIN structures to improve conversion efficiency. Numerical simulations are conducted for the energy deposition of beta particles along the thickness direction in semiconductors. Based on this, 63 Ni-radiation GaAs batteries with PIN and P + PINN + structures are designed and fabricated to experimentally verify the proposed design. It turns out that the conversion efficiency of the betavoltaic battery with the proposed P + PINN + structure is about 1.45 times higher than that with the traditional PIN structure. (cross-disciplinary physics and related areas of science and technology)

A biomimetic redox flow battery based on flavin mononucleotide

Science.gov (United States)

Orita, Akihiro; Verde, Michael G.; Sakai, Masanori; Meng, Ying Shirley

2016-10-01

The versatility in design of redox flow batteries makes them apt to efficiently store energy in large-scale applications at low cost. The discovery of inexpensive organic electroactive materials for use in aqueous flow battery electrolytes is highly attractive, but is thus far limited. Here we report on a flow battery using an aqueous electrolyte based on the sodium salt of flavin mononucleotide. Flavins are highly versatile electroactive molecules, which catalyse a multitude of redox reactions in biological systems. We use nicotinamide (vitamin B3) as a hydrotropic agent to enhance the water solubility of flavin mononucleotide. A redox flow battery using flavin mononucleotide negative and ferrocyanide positive electrolytes in strong base shows stable cycling performance, with over 99% capacity retention over the course of 100 cycles. We hypothesize that this is enabled due to the oxidized and reduced forms of FMN-Na being stabilized by resonance structures.

Thermo-electrochemical model for forced convection air cooling of a lithium-ion battery module

International Nuclear Information System (INIS)

Tong, Wei; Somasundaram, Karthik; Birgersson, Erik; Mujumdar, Arun S.; Yap, Christopher

2016-01-01

Highlights: • Coupled thermal-electrochemical model for a Li-ion battery module resolving every functional layer in all cells. • Parametric analysis of forced convection air cooling of Li-ion battery module with a detailed multi-scale model. • Reversing/reciprocating airflow for Li-ion battery module thermal management provides uniform temperature distribution. - Abstract: Thermal management is critical for safe and reliable operation of lithium-ion battery systems. In this study, a one-dimensional thermal-electrochemical model of lithium-ion battery interactively coupled with a two-dimensional thermal-fluid conjugate model for forced convection air cooling of a lithium-ion battery module is presented and solved numerically. This coupled approach makes the model more unique and detailed as transport inside each cell in the battery module is solved for and thus covering multiple length and time scales. The effect of certain design and operating parameters of the thermal management system on the performance of the battery module is assessed using the coupled model. It is found that a lower temperature increase of the battery module can be achieved by either increasing the inlet air velocity or decreasing the distance between the cells. Higher air inlet velocity, staggered cell arrangement or a periodic reversal airflow of high reversal frequency results in a more uniform temperature distribution in the module. However, doing so increases the parasitic load as well as the volume of the battery module whence a trade-off should be taken into account between these parameters.

An enhanced dynamic model of battery using genetic algorithm suitable for photovoltaic applications

International Nuclear Information System (INIS)

Blaifi, S.; Moulahoum, S.; Colak, I.; Merrouche, W.

2016-01-01

Highlights: • We proposed a developed dynamic battery model suitable for photovoltaic systems. • We used genetic algorithm optimization method to find parameters that gives minimized error. • The validation was carried out with real measurements from stand-alone photovoltaic string. - Abstract: Modeling of batteries in photovoltaic systems has been a major issue related to the random dynamic regime imposed by the changes of solar irradiation and ambient temperature added to the complexity of battery electrochemical and electrical behaviors. However, various approaches have been proposed to model the battery behavior by predicting from detailed electrochemical, electrical or analytical models to high-level stochastic models. In this paper, an improvement of dynamic electrical battery model is proposed by automatic parameter extraction using genetic algorithm in order to give usefulness and future implementation for practical application. It is highlighted that the enhancement of 21 values of the parameters of CEIMAT model presents a good agreement with real measurements for different modes like charge or discharge and various conditions.

Experimental verification of a thermal equivalent circuit dynamic model on an extended range electric vehicle battery pack

Science.gov (United States)

Ramotar, Lokendra; Rohrauer, Greg L.; Filion, Ryan; MacDonald, Kathryn

2017-03-01

The development of a dynamic thermal battery model for hybrid and electric vehicles is realized. A thermal equivalent circuit model is created which aims to capture and understand the heat propagation from the cells through the entire pack and to the environment using a production vehicle battery pack for model validation. The inclusion of production hardware and the liquid battery thermal management system components into the model considers physical and geometric properties to calculate thermal resistances of components (conduction, convection and radiation) along with their associated heat capacity. Various heat sources/sinks comprise the remaining model elements. Analog equivalent circuit simulations using PSpice are compared to experimental results to validate internal temperature nodes and heat rates measured through various elements, which are then employed to refine the model further. Agreement with experimental results indicates the proposed method allows for a comprehensive real-time battery pack analysis at little computational expense when compared to other types of computer based simulations. Elevated road and ambient conditions in Mesa, Arizona are simulated on a parked vehicle with varying quiescent cooling rates to examine the effect on the diurnal battery temperature for longer term static exposure. A typical daily driving schedule is also simulated and examined.

A biomimetic redox flow battery based on flavin mononucleotide

OpenAIRE

Orita, A; Verde, MG; Sakai, M; Meng, YS

2016-01-01

The versatility in design of redox flow batteries makes them apt to efficiently store energy in large-scale applications at low cost. The discovery of inexpensive organic electroactive materials for use in aqueous flow battery electrolytes is highly attractive, but is thus far limited. Here we report on a flow battery using an aqueous electrolyte based on the sodium salt of flavin mononucleotide. Flavins are highly versatile electroactive molecules, which catalyse a multitude of redox reactio...

Multi-Node Thermal System Model for Lithium-Ion Battery Packs: Preprint

Energy Technology Data Exchange (ETDEWEB)

Shi, Ying; Smith, Kandler; Wood, Eric; Pesaran, Ahmad

2015-09-14

Temperature is one of the main factors that controls the degradation in lithium ion batteries. Accurate knowledge and control of cell temperatures in a pack helps the battery management system (BMS) to maximize cell utilization and ensure pack safety and service life. In a pack with arrays of cells, a cells temperature is not only affected by its own thermal characteristics but also by its neighbors, the cooling system and pack configuration, which increase the noise level and the complexity of cell temperatures prediction. This work proposes to model lithium ion packs thermal behavior using a multi-node thermal network model, which predicts the cell temperatures by zones. The model was parametrized and validated using commercial lithium-ion battery packs. neighbors, the cooling system and pack configuration, which increase the noise level and the complexity of cell temperatures prediction. This work proposes to model lithium ion packs thermal behavior using a multi-node thermal network model, which predicts the cell temperatures by zones. The model was parametrized and validated using commercial lithium-ion battery packs.

Battery Aging, Battery Charging and the Kinetic Battery Model : A First Exploration

NARCIS (Netherlands)

Jongerden, Marijn R.; Haverkort, Boudewijn R.; Bertrand, Nathalie; Bortolussi, Luca

2017-01-01

Rechargeable batteries are omnipresent and will be used more and more, for instance for wearables devices, electric vehicles or domestic energy storage. However, batteries can deliver power only for a limited time span. They slowly degrade with every charge-discharge cycle. This degradation needs to

Multiscale modeling and characterization for performance and safety of lithium-ion batteries

International Nuclear Information System (INIS)

Pannala, S.; Turner, J. A.; Allu, S.; Elwasif, W. R.; Kalnaus, S.; Simunovic, S.; Kumar, A.; Billings, J. J.; Wang, H.; Nanda, J.

2015-01-01

Lithium-ion batteries are highly complex electrochemical systems whose performance and safety are governed by coupled nonlinear electrochemical-electrical-thermal-mechanical processes over a range of spatiotemporal scales. Gaining an understanding of the role of these processes as well as development of predictive capabilities for design of better performing batteries requires synergy between theory, modeling, and simulation, and fundamental experimental work to support the models. This paper presents the overview of the work performed by the authors aligned with both experimental and computational efforts. In this paper, we describe a new, open source computational environment for battery simulations with an initial focus on lithium-ion systems but designed to support a variety of model types and formulations. This system has been used to create a three-dimensional cell and battery pack models that explicitly simulate all the battery components (current collectors, electrodes, and separator). The models are used to predict battery performance under normal operations and to study thermal and mechanical safety aspects under adverse conditions. This paper also provides an overview of the experimental techniques to obtain crucial validation data to benchmark the simulations at various scales for performance as well as abuse. We detail some initial validation using characterization experiments such as infrared and neutron imaging and micro-Raman mapping. In addition, we identify opportunities for future integration of theory, modeling, and experiments

Predictive Model Based Battery Constraints for Electric Motor Control within EV Powertrains

NARCIS (Netherlands)

Roşca, B.; Wilkins, S.; Jacob, J.; Hoedemaekers, E.R.G.; Hoek, S.P. van den

2014-01-01

This paper presents a method of predicting the maximum power capability of a Li-Ion battery, to be used for electric motor control within automotive powertrains. As maximum power is highly dependent on battery state, the method consists of a pack level state observer coupled with a predictive

State of Charge Estimation for Lithium-Ion Battery with a Temperature-Compensated Model

Directory of Open Access Journals (Sweden)

Shichun Yang

2017-10-01

Full Text Available Accurate estimation of the state of charge (SOC of batteries is crucial in a battery management system. Many studies on battery SOC estimation have been investigated recently. Temperature is an important factor that affects the SOC estimation accuracy while it is still not adequately addressed at present. This paper proposes a SOC estimator based on a new temperature-compensated model with extended Kalman Filter (EKF. The open circuit voltage (OCV, capacity, and resistance and capacitance (RC parameters in the estimator are temperature dependent so that the estimator can maintain high accuracy at various temperatures. The estimation accuracy decreases when applied in high current continuous discharge, because the equivalent polarization resistance decreases as the discharge current increases. Therefore, a polarization resistance correction coefficient is proposed to tackle this problem. The estimator also demonstrates a good performance in dynamic operating conditions. However, the equivalent circuit model shows huge uncertainty in the low SOC region, so measurement noise variation is proposed to improve the estimation accuracy there.

3-D CFD modeling and experimental testing of thermal behavior of a Li-Ion battery

International Nuclear Information System (INIS)

Gümüşsu, Emre; Ekici, Özgür; Köksal, Murat

2017-01-01

Highlights: • A thermally fully predictive 3-D CFD model is developed for Li-Ion batteries. • Complete flow field around the battery and conduction inside the battery are solved. • Macro-scale thermophysical properties and the entropic term are investigated. • Discharge rate and usage history of the battery are systematically investigated. • Reliability of the model was tested through experimental measurements. - Abstract: In this study, a 3-D computational fluid dynamics model was developed for investigating the thermal behavior of lithium ion batteries under natural convection. The model solves the complete flow field around the battery as well as conduction inside the battery using the well-known heat generation model of Bernardi et al. (1985). The model is thermally fully predictive so it requires only electrical performance parameters of the battery to calculate its temperature during discharging. Using the model, detailed investigation of the effects of the variation of the macro-scale thermophysical properties and the entropic term of the heat generation model was carried out. Results show that specific heat is a critical property that has a significant impact on the simulation results whereas thermal conductivity has relatively minor importance. Moreover, the experimental data can be successfully predicted without taking the entropic term into account in the calculation of the heat generation. The difference between the experimental and predicted battery surface temperature was less than 3 °C for all discharge rates and regardless of the usage history of the battery. The developed model has the potential to be used for the investigation of the thermal behavior of Li-Ion batteries in different packaging configurations under natural and forced convection.

Robustness of SOC Estimation Algorithms for EV Lithium-Ion Batteries against Modeling Errors and Measurement Noise

Directory of Open Access Journals (Sweden)

Xue Li

2015-01-01

Full Text Available State of charge (SOC is one of the most important parameters in battery management system (BMS. There are numerous algorithms for SOC estimation, mostly of model-based observer/filter types such as Kalman filters, closed-loop observers, and robust observers. Modeling errors and measurement noises have critical impact on accuracy of SOC estimation in these algorithms. This paper is a comparative study of robustness of SOC estimation algorithms against modeling errors and measurement noises. By using a typical battery platform for vehicle applications with sensor noise and battery aging characterization, three popular and representative SOC estimation methods (extended Kalman filter, PI-controlled observer, and H∞ observer are compared on such robustness. The simulation and experimental results demonstrate that deterioration of SOC estimation accuracy under modeling errors resulted from aging and larger measurement noise, which is quantitatively characterized. The findings of this paper provide useful information on the following aspects: (1 how SOC estimation accuracy depends on modeling reliability and voltage measurement accuracy; (2 pros and cons of typical SOC estimators in their robustness and reliability; (3 guidelines for requirements on battery system identification and sensor selections.

MATHEMATICAL MODELING OF ELECTROCHEMICAL PROCESSES IN LITHIUM-ION BATTERIES POTENTIALLY STREAMING METHOD

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S. P. Halutin

2014-01-01

Full Text Available Mathematical models in the electrical parameters of physico-chemical processes in lithium-ion batteries are developed. The developed model parameters (discharge mode are identified out of family of discharging curve. By using of the parameters of this model we get the numerically model of lithium-ion battery.

A dynamic performance model for redox-flow batteries involving soluble species

International Nuclear Information System (INIS)

Shah, A.A.; Watt-Smith, M.J.; Walsh, F.C.

2008-01-01

A transient modelling framework for a vanadium redox-flow battery (RFB) is developed and experiments covering a range of vanadium concentration and electrolyte flow rate are conducted. The two-dimensional model is based on a comprehensive description of mass, charge and momentum transport and conservation, and is combined with a global kinetic model for reactions involving vanadium species. The model is validated against the experimental data and is used to study the effects of variations in concentration, electrolyte flow rate and electrode porosity. Extensions to the model and future work are suggested

A degradation-based sorting method for lithium-ion battery reuse.

Directory of Open Access Journals (Sweden)

Hao Chen

Full Text Available In a world where millions of people are dependent on batteries to provide them with convenient and portable energy, battery recycling is of the utmost importance. In this paper, we developed a new method to sort 18650 Lithium-ion batteries in large quantities and in real time for harvesting used cells with enough capacity for battery reuse. Internal resistance and capacity tests were conducted as a basis for comparison with a novel degradation-based method based on X-ray radiographic scanning and digital image contrast computation. The test results indicate that the sorting accuracy of the test cells is about 79% and the execution time of our algorithm is at a level of 200 milliseconds, making our method a potential real-time solution for reusing the remaining capacity in good used cells.

Generic modelling framework for economic analysis of battery systems

DEFF Research Database (Denmark)

You, Shi; Rasmussen, Claus Nygaard

2011-01-01

opportunities, a generic modelling framework is proposed to handle this task. This framework outlines a set of building blocks which are necessary for carrying out the economic analysis of various BS applications. Further, special focus is given on describing how to use the rainflow cycle counting algorithm...... for battery cycle life estimation, since the cycle life plays a central role in the economic analysis of BS. To illustrate the modelling framework, a case study using a Sodium Sulfur Battery (NAS) system with 5-minute regulating service is performed. The economic performances of two dispatch scenarios, a so......Deregulated electricity markets provide opportunities for Battery Systems (BS) to participate in energy arbitrage and ancillary services (regulation, operating reserves, contingency reserves, voltage regulation, power quality etc.). To evaluate the economic viability of BS with different business...

A Generalized SOC-OCV Model for Lithium-Ion Batteries and the SOC Estimation for LNMCO Battery

Directory of Open Access Journals (Sweden)

Caiping Zhang

2016-11-01

Full Text Available A state-of-charge (SOC versus open-circuit-voltage (OCV model developed for batteries should preferably be simple, especially for real-time SOC estimation. It should also be capable of representing different types of lithium-ion batteries (LIBs, regardless of temperature change and battery degradation. It must therefore be generic, robust and adaptive, in addition to being accurate. These challenges have now been addressed by proposing a generalized SOC-OCV model for representing a few most widely used LIBs. The model is developed from analyzing electrochemical processes of the LIBs, before arriving at the sum of a logarithmic, a linear and an exponential function with six parameters. Values for these parameters are determined by a nonlinear estimation algorithm, which progressively shows that only four parameters need to be updated in real time. The remaining two parameters can be kept constant, regardless of temperature change and aging. Fitting errors demonstrated with different types of LIBs have been found to be within 0.5%. The proposed model is thus accurate, and can be flexibly applied to different LIBs, as verified by hardware-in-the-loop simulation designed for real-time SOC estimation.

Catastrophic event modeling. [lithium thionyl chloride batteries

Science.gov (United States)

Frank, H. A.

1981-01-01

A mathematical model for the catastrophic failures (venting or explosion of the cell) in lithium thionyl chloride batteries is presented. The phenomenology of the various processes leading to cell failure is reviewed.

Supervised chaos genetic algorithm based state of charge determination for LiFePO4 batteries in electric vehicles

Science.gov (United States)

Shen, Yanqing

2018-04-01

LiFePO4 battery is developed rapidly in electric vehicle, whose safety and functional capabilities are influenced greatly by the evaluation of available cell capacity. Added with adaptive switch mechanism, this paper advances a supervised chaos genetic algorithm based state of charge determination method, where a combined state space model is employed to simulate battery dynamics. The method is validated by the experiment data collected from battery test system. Results indicate that the supervised chaos genetic algorithm based state of charge determination method shows great performance with less computation complexity and is little influenced by the unknown initial cell state.

Environmental impact assessment and end-of-life treatment policy analysis for Li-ion batteries and Ni-MH batteries.

Science.gov (United States)

Yu, Yajuan; Chen, Bo; Huang, Kai; Wang, Xiang; Wang, Dong

2014-03-18

Based on Life Cycle Assessment (LCA) and Eco-indicator 99 method, a LCA model was applied to conduct environmental impact and end-of-life treatment policy analysis for secondary batteries. This model evaluated the cycle, recycle and waste treatment stages of secondary batteries. Nickel-Metal Hydride (Ni-MH) batteries and Lithium ion (Li-ion) batteries were chosen as the typical secondary batteries in this study. Through this research, the following results were found: (1) A basic number of cycles should be defined. A minimum cycle number of 200 would result in an obvious decline of environmental loads for both battery types. Batteries with high energy density and long life expectancy have small environmental loads. Products and technology that help increase energy density and life expectancy should be encouraged. (2) Secondary batteries should be sorted out from municipal garbage. Meanwhile, different types of discarded batteries should be treated separately under policies and regulations. (3) The incineration rate has obvious impact on the Eco-indicator points of Nickel-Metal Hydride (Ni-MH) batteries. The influence of recycle rate on Lithium ion (Li-ion) batteries is more obvious. These findings indicate that recycling is the most promising direction for reducing secondary batteries' environmental loads. The model proposed here can be used to evaluate environmental loads of other secondary batteries and it can be useful for proposing policies and countermeasures to reduce the environmental impact of secondary batteries.

State of Charge Balancing Control of a Multi-Functional Battery Energy Storage System Based on a 11-Level Cascaded Multilevel PWM Converter

DEFF Research Database (Denmark)

Wang, Songcen; Teodorescu, Remus; Máthé, Lászlo

2015-01-01

This paper focuses on modeling and SOC (State of Charge) balancing control of lithium-ion battery energy storage system based on cascaded multilevel converter for both grid integration and electric vehicle propulsion applications. The equivalent electrical circuit model of lithium-ion battery...

A Novel Electric Bicycle Battery Monitoring System Based on Android Client

Directory of Open Access Journals (Sweden)

Chuanxue Song

2017-01-01

Full Text Available The battery monitoring system (BMS plays a crucial role in maintaining the safe operation of the lithium battery electric bicycle and prolonging the life of the battery pack. This paper designed a set of new battery monitoring systems based on the Android system and ARM single-chip microcomputer to enable direct management of the lithium battery pack and convenient monitoring of the state of the battery pack. The BMS realizes the goal of monitoring the voltage, current, and ambient temperature of lithium batteries, estimating the state of charge (SOC and state of health (SOH, protecting the battery from abuse during charging or discharging, and ensuring the consistency of the batteries by integrating the passive equalization circuit. The BMS was proven effective and feasible through several tests, including charging/discharging, estimation accuracy, and communication tests. The results indicated that the BMS could be used in the design and application of the electric bicycle.

Innovative model-based flow rate optimization for vanadium redox flow batteries

Science.gov (United States)

König, S.; Suriyah, M. R.; Leibfried, T.

2016-11-01

In this paper, an innovative approach is presented to optimize the flow rate of a 6-kW vanadium redox flow battery with realistic stack dimensions. Efficiency is derived using a multi-physics battery model and a newly proposed instantaneous efficiency determination technique. An optimization algorithm is applied to identify optimal flow rates for operation points defined by state-of-charge (SoC) and current. The proposed method is evaluated against the conventional approach of applying Faraday's first law of electrolysis, scaled to the so-called flow factor. To make a fair comparison, the flow factor is also optimized by simulating cycles with different charging/discharging currents. It is shown through the obtained results that the efficiency is increased by up to 1.2% points; in addition, discharge capacity is also increased by up to 1.0 kWh or 5.4%. Detailed loss analysis is carried out for the cycles with maximum and minimum charging/discharging currents. It is shown that the proposed method minimizes the sum of losses caused by concentration over-potential, pumping and diffusion. Furthermore, for the deployed Nafion 115 membrane, it is observed that diffusion losses increase with stack SoC. Therefore, to decrease stack SoC and lower diffusion losses, a higher flow rate during charging than during discharging is reasonable.

An integrated model of the lithium/thionyl chloride battery

Energy Technology Data Exchange (ETDEWEB)

Jungst, R.G.; Nagasubramanian, G.; Ingersoll, D.; O`Gorman, C.C.; Paez, T.L. [Sandia National Labs., Albuquerque, NM (United States); Jain, M.; Weidner, J.W. [Univ. of South Carolina, Columbia, SC (United States)

1998-06-08

The desire to reduce the time and cost of design engineering on new components or to validate existing designs in new applications is stimulating the development of modeling and simulation tools. The authors are applying a model-based design approach to low and moderate rate versions of the Li/SOCl{sub 2} D-size cell with success. Three types of models are being constructed and integrated to achieve maximum capability and flexibility in the final simulation tool. A phenomenology based electrochemical model links performance and the cell design, chemical processes, and material properties. An artificial neural network model improves computational efficiency and fills gaps in the simulation capability when fundamental cell parameters are too difficult to measure or the forms of the physical relationships are not understood. Finally, a PSpice-based model provides a simple way to test the cell under realistic electrical circuit conditions. Integration of these three parts allows a complete link to be made between fundamental battery design characteristics and the performance of the rest of the electrical subsystem.

Electric Vehicle Based Battery Storages for Future Power System Regulation Services

DEFF Research Database (Denmark)

Pillai, Jayakrishnan Radhakrishna; Bak-Jensen, Birgitte

2009-01-01

supplying the reserve power requirements. This limited regulation services from conventional generators in the future power system calls for other new reserve power solutions like Electric Vehicle (EV) based battery storages. A generic aggregated EV based battery storage for long-term dynamic load frequency...

Redox Species-Based Electrolytes for Advanced Rechargeable Lithium Ion Batteries

KAUST Repository

Ming, Jun

2016-08-15

Seeking high-capacity cathodes has become an intensive effort in lithium ion battery research; however, the low energy density still remains a major issue for sustainable handheld devices and vehicles. Herein, we present a new strategy of integrating a redox species-based electrolyte in batteries to boost their performance. Taking the olivine LiFePO4-based battery as an example, the incorporation of redox species (i.e., polysulfide of Li2S8) in the electrolyte results in much lower polarization and superior stability, where the dissociated Li+/Sx2– can significantly speed up the lithium diffusion. More importantly, the presence of the S82–/S2– redox reaction further contributes extra capacity, making a completely new LiFePO4/Li2Sx hybrid battery with a high energy density of 1124 Wh kgcathode–1 and a capacity of 442 mAh gcathode–1. The marriage of appropriate redox species in an electrolyte for a rechargeable battery is an efficient and scalable approach for obtaining higher energy density storage devices.

State of Charge Estimation Based on Microscopic Driving Parameters for Electric Vehicle's Battery

Directory of Open Access Journals (Sweden)

Enjian Yao

2013-01-01

Full Text Available Recently, battery-powered electric vehicle (EV has received wide attention due to less pollution during use, low noise, and high energy efficiency and is highly expected to improve urban air quality and then mitigate energy and environmental pressure. However, the widespread use of EV is still hindered by limited battery capacity and relatively short cruising range. This paper aims to propose a state of charge (SOC estimation method for EV’s battery necessary for route planning and dynamic route guidance, which can help EV drivers to search for the optimal energy-efficient routes and to reduce the risk of running out of electricity before arriving at the destination or charging station. Firstly, by analyzing the variation characteristics of power consumption rate with initial SOC and microscopic driving parameters (instantaneous speed and acceleration, a set of energy consumption rate models are established according to different operation modes. Then, the SOC estimation model is proposed based on the presented EV power consumption model. Finally, by comparing the estimated SOC with the measured SOC, the proposed SOC estimation method is proved to be highly accurate and effective, which can be well used in EV route planning and navigation systems.

Online Estimation of Model Parameters and State of Charge of LiFePO4 Batteries Using a Novel Open-Circuit Voltage at Various Ambient Temperatures

Directory of Open Access Journals (Sweden)

Fei Feng

2015-04-01

Full Text Available This study describes an online estimation of the model parameters and state of charge (SOC of lithium iron phosphate batteries in electric vehicles. A widely used SOC estimator is based on the dynamic battery model with predeterminate parameters. However, model parameter variances that follow with their varied operation temperatures can result in errors in estimating battery SOC. To address this problem, a battery online parameter estimator is presented based on an equivalent circuit model using an adaptive joint extended Kalman filter algorithm. Simulations based on actual data are established to verify accuracy and stability in the regression of model parameters. Experiments are also performed to prove that the proposed estimator exhibits good reliability and adaptability under different loading profiles with various temperatures. In addition, open-circuit voltage (OCV is used to estimate SOC in the proposed algorithm. However, the OCV based on the proposed online identification includes a part of concentration polarization and hysteresis, which is defined as parametric identification-based OCV (OCVPI. Considering the temperature factor, a novel OCV–SOC relationship map is established by using OCVPI under various temperatures. Finally, a validating experiment is conducted based on the consecutive loading profiles. Results indicate that our method is effective and adaptable when a battery operates at different ambient temperatures.

Electrochemical-thermal modeling and microscale phase change for passive internal thermal management of lithium ion batteries.

Energy Technology Data Exchange (ETDEWEB)

Fuller, Thomas F. (Georgia Institute of Technology, Atlanta, GA); Bandhauer, Todd (Georgia Institute of Technology, Atlanta, GA); Garimella, Srinivas (Georgia Institute of Technology, Atlanta, GA)

2012-01-01

A fully coupled electrochemical and thermal model for lithium-ion batteries is developed to investigate the impact of different thermal management strategies on battery performance. In contrast to previous modeling efforts focused either exclusively on particle electrochemistry on the one hand or overall vehicle simulations on the other, the present work predicts local electrochemical reaction rates using temperature-dependent data on commercially available batteries designed for high rates (C/LiFePO{sub 4}) in a computationally efficient manner. Simulation results show that conventional external cooling systems for these batteries, which have a low composite thermal conductivity ({approx}1 W/m-K), cause either large temperature rises or internal temperature gradients. Thus, a novel, passive internal cooling system that uses heat removal through liquid-vapor phase change is developed. Although there have been prior investigations of phase change at the microscales, fluid flow at the conditions expected here is not well understood. A first-principles based cooling system performance model is developed and validated experimentally, and is integrated into the coupled electrochemical-thermal model for assessment of performance improvement relative to conventional thermal management strategies. The proposed cooling system passively removes heat almost isothermally with negligible thermal resistances between the heat source and cooling fluid. Thus, the minimization of peak temperatures and gradients within batteries allow increased power and energy densities unencumbered by thermal limitations.

Influence of Li-ion Battery Models in the Sizing of Hybrid Storage Systems with Supercapacitors

DEFF Research Database (Denmark)

Pinto, Claudio; Barreras, Jorge Varela; de Castro, Ricardo

2014-01-01

This paper presents a comparative study of the influence of different aggregated electrical circuit battery models in the sizing process of a hybrid energy storage system (ESS), composed by Li-ion batteries and supercapacitors (SCs). The aim is to find the number of cells required to propel...... a certain vehicle over a predefined driving cycle. During this process, three battery models will be considered. The first consists in a linear static zeroeth order battery model over a restricted operating window. The second is a non-linear static model, while the third takes into account first......-order dynamics of the battery. Simulation results demonstrate that the adoption of a more accurate battery model in the sizing of hybrid ESSs prevents over-sizing, leading to a reduction in the number of cells of up to 29%, and a cost decrease of up to 10%....

Multi-physics Model for the Aging Prediction of a Vanadium Redox Flow Battery System

International Nuclear Information System (INIS)

Merei, Ghada; Adler, Sophie; Magnor, Dirk; Sauer, Dirk Uwe

2015-01-01

Highlights: • Present a multi-physics model of vanadium redox-flow battery. • This model is essential for aging prediction. • It is applicable for VRB system of different power and capacity ratings. • Good results comparing with current research in this field. - Abstract: The all-vanadium redox-flow battery is an attractive candidate to compensate the fluctuations of non-dispatchable renewable energy generation. While several models for vanadium redox batteries have been described yet, no model has been published, which is adequate for the aging prediction. Therefore, the present paper presents a multi-physics model which determines all parameters that are essential for an aging prediction. In a following paper, the corresponding aging model of vanadium redox flow battery (VRB) is described. The model combines existing models for the mechanical losses and temperature development with new approaches for the batteries side reactions. The model was implemented in Matlab/Simulink. The modeling results presented in the paper prove to be consistent with the experimental results of other research groups

Environmental Impact Assessment and End-of-Life Treatment Policy Analysis for Li-Ion Batteries and Ni-MH Batteries

Directory of Open Access Journals (Sweden)

Yajuan Yu

2014-03-01

Full Text Available Based on Life Cycle Assessment (LCA and Eco-indicator 99 method, a LCA model was applied to conduct environmental impact and end-of-life treatment policy analysis for secondary batteries. This model evaluated the cycle, recycle and waste treatment stages of secondary batteries. Nickel-Metal Hydride (Ni-MH batteries and Lithium ion (Li-ion batteries were chosen as the typical secondary batteries in this study. Through this research, the following results were found: (1 A basic number of cycles should be defined. A minimum cycle number of 200 would result in an obvious decline of environmental loads for both battery types. Batteries with high energy density and long life expectancy have small environmental loads. Products and technology that help increase energy density and life expectancy should be encouraged. (2 Secondary batteries should be sorted out from municipal garbage. Meanwhile, different types of discarded batteries should be treated separately under policies and regulations. (3 The incineration rate has obvious impact on the Eco-indicator points of Nickel-Metal Hydride (Ni-MH batteries. The influence of recycle rate on Lithium ion (Li-ion batteries is more obvious. These findings indicate that recycling is the most promising direction for reducing secondary batteries’ environmental loads. The model proposed here can be used to evaluate environmental loads of other secondary batteries and it can be useful for proposing policies and countermeasures to reduce the environmental impact of secondary batteries.

Environmental Impact Assessment and End-of-Life Treatment Policy Analysis for Li-Ion Batteries and Ni-MH Batteries

Science.gov (United States)

Yu, Yajuan; Chen, Bo; Huang, Kai; Wang, Xiang; Wang, Dong

2014-01-01

Based on Life Cycle Assessment (LCA) and Eco-indicator 99 method, a LCA model was applied to conduct environmental impact and end-of-life treatment policy analysis for secondary batteries. This model evaluated the cycle, recycle and waste treatment stages of secondary batteries. Nickel-Metal Hydride (Ni-MH) batteries and Lithium ion (Li-ion) batteries were chosen as the typical secondary batteries in this study. Through this research, the following results were found: (1) A basic number of cycles should be defined. A minimum cycle number of 200 would result in an obvious decline of environmental loads for both battery types. Batteries with high energy density and long life expectancy have small environmental loads. Products and technology that help increase energy density and life expectancy should be encouraged. (2) Secondary batteries should be sorted out from municipal garbage. Meanwhile, different types of discarded batteries should be treated separately under policies and regulations. (3) The incineration rate has obvious impact on the Eco-indicator points of Nickel-Metal Hydride (Ni-MH) batteries. The influence of recycle rate on Lithium ion (Li-ion) batteries is more obvious. These findings indicate that recycling is the most promising direction for reducing secondary batteries’ environmental loads. The model proposed here can be used to evaluate environmental loads of other secondary batteries and it can be useful for proposing policies and countermeasures to reduce the environmental impact of secondary batteries. PMID:24646862

Geometric Process-Based Maintenance and Optimization Strategy for the Energy Storage Batteries

Directory of Open Access Journals (Sweden)

Yan Li

2016-01-01

Full Text Available Renewable energy is critical for improving energy structure and reducing environment pollution. But its strong fluctuation and randomness have a serious effect on the stability of the microgrid without the coordination of the energy storage batteries. The main factors that influence the development of the energy storage system are the lack of valid operation and maintenance management as well as the cost control. By analyzing the typical characteristics of the energy storage batteries in their life cycle, the geometric process-based model including the deteriorating system and the improving system is firstly built for describing the operation process, the preventive maintenance process, and the corrective maintenance process. In addition, this paper proposes an optimized management strategy, which aims to minimize the long-run average cost of the energy storage batteries by defining the time interval of the detection and preventive maintenance process as well as the optimal corrective maintenance times, subjected to the state of health and the reliability conditions. The simulation is taken under the built model by applying the proposed energy storage batteries’ optimized management strategy, which verifies the effectiveness and applicability of the management strategy, denoting its obvious practicality on the current application.

Battery Management System—Balancing Modularization Based on a Single Switched Capacitor and Bi-Directional DC/DC Converter with the Auxiliary Battery

Directory of Open Access Journals (Sweden)

Mohamed Daowd

2014-04-01

Full Text Available Lithium-based batteries are considered as the most advanced batteries technology, which can be designed for high energy or high power storage systems. However, the battery cells are never fully identical due to the fabrication process, surrounding environment factors and differences between the cells tend to grow if no measures are taken. In order to have a high performance battery system, the battery cells should be continuously balanced for maintain the variation between the cells as small as possible. Without an appropriate balancing system, the individual cell voltages will differ over time and battery system capacity will decrease quickly. These issues will limit the electric range of the electric vehicle (EV and some cells will undergo higher stress, whereby the cycle life of these cells will be shorter. Quite a lot of cell balancing/equalization topologies have been previously proposed. These balancing topologies can be categorized into passive and active balancing. Active topologies are categorized according to the active element used for storing the energy such as capacitor and/or inductive component as well as controlling switches or converters. This paper proposes an intelligent battery management system (BMS including a battery pack charging and discharging control with a battery pack thermal management system. The BMS user input/output interfacing. The battery balancing system is based on battery pack modularization architecture. The proposed modularized balancing system has different equalization systems that operate inside and outside the modules. Innovative single switched capacitor (SSC control strategy is proposed to balance between the battery cells in the module (inside module balancing, IMB. Novel utilization of isolated bidirectional DC/DC converter (IBC is proposed to balance between the modules with the aid of the EV auxiliary battery (AB. Finally an experimental step-up has been implemented for the validation of the

Discrimination of Li-ion batteries based on Hamming network using discharging-charging voltage pattern recognition for improved state-of-charge estimation

Energy Technology Data Exchange (ETDEWEB)

Kim, Jonghoon; Lee, Seongjun; Cho, B.H. [Power Electronics System Laboratory, School of Electrical Engineering and Computer Science, Seoul National University, Seoul 151-744 (Korea, Republic of)

2011-02-15

Differences in electrochemical characteristics among Li-ion batteries and factors such as temperature and ageing result in erroneous state-of-charge (SoC) estimation when using the existing extended Kalman filter (EKF) algorithm. This study presents an application of the Hamming neural network to the identification of suitable battery model parameters for improved SoC estimation. The discharging-charging voltage (DCV) patterns of ten fresh Li-ion batteries are measured, together with the battery parameters, as representative patterns. Through statistical analysis, the Hamming network is applied for identification of the representative DCV pattern that matches most closely of the pattern of the arbitrary battery to be measured. Model parameters of the representative battery are then applied to estimate the SoC of the arbitrary battery using the EKF. This avoids the need for repeated parameter measurement. Using model parameters selected by the proposed method, all SoC estimates (off-line and on-line) based on the EKF are within {+-}5% of the values estimated by ampere-hour counting. (author)

Life Prediction Model for Grid-Connected Li-ion Battery Energy Storage System: Preprint

Energy Technology Data Exchange (ETDEWEB)

Smith, Kandler A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Saxon, Aron R [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Keyser, Matthew A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Lundstrom, Blake R [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Cao, Ziwei [SunPower Corporation; Roc, Albert [SunPower Corp.

2017-08-25

Life Prediction Model for Grid-Connected Li-ion Battery Energy Storage System: Preprint Lithium-ion (Li-ion) batteries are being deployed on the electrical grid for a variety of purposes, such as to smooth fluctuations in solar renewable power generation. The lifetime of these batteries will vary depending on their thermal environment and how they are charged and discharged. To optimal utilization of a battery over its lifetime requires characterization of its performance degradation under different storage and cycling conditions. Aging tests were conducted on commercial graphite/nickel-manganese-cobalt (NMC) Li-ion cells. A general lifetime prognostic model framework is applied to model changes in capacity and resistance as the battery degrades. Across 9 aging test conditions from 0oC to 55oC, the model predicts capacity fade with 1.4 percent RMS error and resistance growth with 15 percent RMS error. The model, recast in state variable form with 8 states representing separate fade mechanisms, is used to extrapolate lifetime for example applications of the energy storage system integrated with renewable photovoltaic (PV) power generation.

Multiphysics Modelling of Sodium Sulfur Battery

Science.gov (United States)

Mason, Jerry Hunter

Due to global climate change and the desire to decrease greenhouse gas emissions, large scale energy storage has become a critical issue. Renewable energy sources such as wind and solar will not be a viable energy source unless the storage problem is solved. One of the practical and cost effective solutions for this problem is sodium sulfur batteries. These batteries are comprised of liquid electrode materials suspended in porous media and operate at relatively high temperatures (>300°C). The sodium anode and the sulfur/sodium-polysulfide cathode are separated by a solid electrolyte made of beta-alumina or NASICON material. Due to the use of porous materials in the electrodes, capillary pressure and the combination of capillary action and gravity become important. Capillary pressure has a strong dependence on the wetting phase (liquid electrode material) saturation; therefore sharp concentration gradients can occur between the inert gas and the electrode liquid, especially within the cathode. These concentration gradients can have direct impacts on the electrodynamics of the battery as they may produce areas of high electrical potential variation, which can decrease efficiency and even cause failures. Then, thermal management also becomes vital since the electrochemistry and material properties are sensitive to temperature gradients. To investigate these phenomena in detail and to attempt to improve upon battery design a multi-dimensional, multi-phase code has been developed and validated in this study. Then a porous media flow model is implemented. Transport equations for charge, mass and heat are solved in a time marching fashion using finite volume method. Material properties are calculated and updated as a function of time. The porous media model is coupled with the continuity equation and a separate diffusion equation for the liquid sodium in the melt. The total mass transport model is coupled with charge transport via Faraday's law. Results show that

State of charge estimation of lithium-ion batteries based on an improved parameter identification method

International Nuclear Information System (INIS)

Xia, Bizhong; Chen, Chaoren; Tian, Yong; Wang, Mingwang; Sun, Wei; Xu, Zhihui

2015-01-01

The SOC (state of charge) is the most important index of the battery management systems. However, it cannot be measured directly with sensors and must be estimated with mathematical techniques. An accurate battery model is crucial to exactly estimate the SOC. In order to improve the model accuracy, this paper presents an improved parameter identification method. Firstly, the concept of polarization depth is proposed based on the analysis of polarization characteristics of the lithium-ion batteries. Then, the nonlinear least square technique is applied to determine the model parameters according to data collected from pulsed discharge experiments. The results show that the proposed method can reduce the model error as compared with the conventional approach. Furthermore, a nonlinear observer presented in the previous work is utilized to verify the validity of the proposed parameter identification method in SOC estimation. Finally, experiments with different levels of discharge current are carried out to investigate the influence of polarization depth on SOC estimation. Experimental results show that the proposed method can improve the SOC estimation accuracy as compared with the conventional approach, especially under the conditions of large discharge current. - Highlights: • The polarization characteristics of lithium-ion batteries are analyzed. • The concept of polarization depth is proposed to improve model accuracy. • A nonlinear least square technique is applied to determine the model parameters. • A nonlinear observer is used as the SOC estimation algorithm. • The validity of the proposed method is verified by experimental results.

Thermal modeling. Application to lithium batteries; Modelisation thermique. Application aux accumulateurs lithium

Energy Technology Data Exchange (ETDEWEB)

Alexandre, A. [Ecole Nationale Superieure de Mecanique et d`Aerotechnique (ENSMA), 86 - Poitiers (France); Flament, P. [SAFT, 33 - Bordeaux (France); Marolleau, T. [SAFT, Advanced and Industrial Battery Group, 86 - Poitiers (France); Guiot, T.; Lefriec, C. [TSR Futuropolis, 86 - Chasseneuil du Poitou (France)

1996-12-31

The thermal modeling of electrochemical batteries is today an integral part of the design and validation operations of new products. The Li-ion pair allows to increase the power density of batteries but leads to higher heat fluxes during charging-output cycles. Thus, the thermal control has become more crucial and requires the use of modeling. SAFT and TSR companies are involved in this approach and use the ESACAP software. This paper presents this software which uses a nodal method for the modeling of the coupled thermal and electrical processes that take place inside elementary cells and batteries. (J.S.)

Thermal modeling. Application to lithium batteries; Modelisation thermique. Application aux accumulateurs lithium

Energy Technology Data Exchange (ETDEWEB)

Alexandre, A [Ecole Nationale Superieure de Mecanique et d` Aerotechnique (ENSMA), 86 - Poitiers (France); Flament, P [SAFT, 33 - Bordeaux (France); Marolleau, T [SAFT, Advanced and Industrial Battery Group, 86 - Poitiers (France); Guiot, T; Lefriec, C [TSR Futuropolis, 86 - Chasseneuil du Poitou (France)

1997-12-31

The thermal modeling of electrochemical batteries is today an integral part of the design and validation operations of new products. The Li-ion pair allows to increase the power density of batteries but leads to higher heat fluxes during charging-output cycles. Thus, the thermal control has become more crucial and requires the use of modeling. SAFT and TSR companies are involved in this approach and use the ESACAP software. This paper presents this software which uses a nodal method for the modeling of the coupled thermal and electrical processes that take place inside elementary cells and batteries. (J.S.)

Prognostics of Lithium-Ion Batteries Based on Wavelet Denoising and DE-RVM

Science.gov (United States)

Zhang, Chaolong; He, Yigang; Yuan, Lifeng; Xiang, Sheng; Wang, Jinping

2015-01-01

Lithium-ion batteries are widely used in many electronic systems. Therefore, it is significantly important to estimate the lithium-ion battery's remaining useful life (RUL), yet very difficult. One important reason is that the measured battery capacity data are often subject to the different levels of noise pollution. In this paper, a novel battery capacity prognostics approach is presented to estimate the RUL of lithium-ion batteries. Wavelet denoising is performed with different thresholds in order to weaken the strong noise and remove the weak noise. Relevance vector machine (RVM) improved by differential evolution (DE) algorithm is utilized to estimate the battery RUL based on the denoised data. An experiment including battery 5 capacity prognostics case and battery 18 capacity prognostics case is conducted and validated that the proposed approach can predict the trend of battery capacity trajectory closely and estimate the battery RUL accurately. PMID:26413090

A Battery Health Monitoring Framework for Planetary Rovers

Science.gov (United States)

Daigle, Matthew J.; Kulkarni, Chetan Shrikant

2014-01-01

Batteries have seen an increased use in electric ground and air vehicles for commercial, military, and space applications as the primary energy source. An important aspect of using batteries in such contexts is battery health monitoring. Batteries must be carefully monitored such that the battery health can be determined, and end of discharge and end of usable life events may be accurately predicted. For planetary rovers, battery health estimation and prediction is critical to mission planning and decision-making. We develop a model-based approach utilizing computaitonally efficient and accurate electrochemistry models of batteries. An unscented Kalman filter yields state estimates, which are then used to predict the future behavior of the batteries and, specifically, end of discharge. The prediction algorithm accounts for possible future power demands on the rover batteries in order to provide meaningful results and an accurate representation of prediction uncertainty. The framework is demonstrated on a set of lithium-ion batteries powering a rover at NASA.

Life Prediction Model for Grid-Connected Li-ion Battery Energy Storage System

Energy Technology Data Exchange (ETDEWEB)

Smith, Kandler A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Saxon, Aron R [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Keyser, Matthew A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Lundstrom, Blake R [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Cao, Ziwei [SunPower Corporation; Roc, Albert [SunPower Corporation

2017-09-06

Lithium-ion (Li-ion) batteries are being deployed on the electrical grid for a variety of purposes, such as to smooth fluctuations in solar renewable power generation. The lifetime of these batteries will vary depending on their thermal environment and how they are charged and discharged. To optimal utilization of a battery over its lifetime requires characterization of its performance degradation under different storage and cycling conditions. Aging tests were conducted on commercial graphite/nickel-manganese-cobalt (NMC) Li-ion cells. A general lifetime prognostic model framework is applied to model changes in capacity and resistance as the battery degrades. Across 9 aging test conditions from 0oC to 55oC, the model predicts capacity fade with 1.4% RMS error and resistance growth with 15% RMS error. The model, recast in state variable form with 8 states representing separate fade mechanisms, is used to extrapolate lifetime for example applications of the energy storage system integrated with renewable photovoltaic (PV) power generation.

Analysis of reaction and transport processes in zinc air batteries

CERN Document Server

Schröder, Daniel

2016-01-01

This book contains a novel combination of experimental and model-based investigations, elucidating the complex processes inside zinc air batteries. The work presented helps to answer which battery composition and which air-composition should be adjusted to maintain stable and efficient charge/discharge cycling. In detail, electrochemical investigations and X-ray transmission tomography are applied on button cell zinc air batteries and in-house set-ups. Moreover, model-based investigations of the battery anode and the impact of relative humidity, active operation, carbon dioxide and oxygen on zinc air battery operation are presented. The techniques used in this work complement each other well and yield an unprecedented understanding of zinc air batteries. The methods applied are adaptable and can potentially be applied to gain further understanding of other metal air batteries. Contents Introduction on Zinc Air Batteries Characterizing Reaction and Transport Processes Identifying Factors for Long-Term Stable O...

Comparison of Parametrization Techniques for an Electrical Circuit Model of Lithium-Sulfur Batteries

DEFF Research Database (Denmark)

Knap, Vaclav; Stroe, Daniel Loan; Teodorescu, Remus

2015-01-01

on the comparison of different parametrization methods of electrical circuit models (ECMs) for Li-S batteries. These methods are used to parametrize an ECM based on laboratory measurements performed on a Li-S pouch cell. Simulation results of ECMs are presented and compared against measurement values...

Economic considerations of battery recycling based on the Recytec process

Science.gov (United States)

Ammann, Pierre

The Recytec process is successfully operated on a continuous industrial base since autumn 1994. All the products are regularly re-used without any problems and environmental limits are fully respected. The European Community Battery Directive is valid since many years and only a few countries like Switzerland and The Netherlands have implemented it in national guidelines. In the meantime, battery producers have accepted the necessity of the recycling of mercury-free batteries in order to prevent the contamination of municipal waste streams by other heavy metals, such as zinc and cadmium. Recycling processes like the Recytec process are considered by the battery producers as highly expensive and they are looking for cheaper alternatives. Steel works are confronted with a market change and have to produce less quantities of better quality steels with more stringent environmental limits. The electric arc furnace (EAF), one of the chosen battery destruction techniques, is producing 20% of the European steel. Even if the battery mixes contain only mercury-free batteries, the residual mercury content and the zinc concentration will be too high to insure a good steel quality, if all collected batteries will be fed in EAF. In Waelz kilns (production of zinc oxide concentrates for zinc producers) the situation is the same with regard to the residual mercury concentration and environmental limits. Sorting technologies for the separation of battery mixes into the different battery chemistries will presently fail because the re-users of these sorted mercury-free batteries are not able to accept raw waste batteries but they are interested in some fractions of them. This means that in any case pretreatment is an unavoidable step before selective reclamation of waste batteries. The Recytec process is the low-cost partner in a global strategy for battery recycling. This process is very flexible and will be able to follow, with slight and inexpensive adaptations of the equipment

Modeling study of a Li–O2 battery with an active cathode

International Nuclear Information System (INIS)

Li, Xianglin; Huang, Jing; Faghri, Amir

2015-01-01

In this study, a new organic lithium oxygen (Li–O 2 ) battery structure is proposed to enhance battery capacity. The electrolyte is forced to recirculate through the cathode and then saturated with oxygen in a tank external to the battery. The forced convection enhances oxygen transport and alleviates the problem of electrode blockage during discharge. A two dimensional, transient, non-isothermal simulation model is developed to study the heat and mass transfer within the battery and validate the proposed design. Results show that this novel active cathode design improves the battery capacity at all discharge current densities. The capacity of the Li–O 2 battery is increased by 15.5 times (from 12.2 mAh g −1 to 201 mAh g −1 ) at the discharge current of 2.0 mA cm −2 when a conventional passive electrode is replaced by the newly designed active electrode. Furthermore, a cathode with non-uniform porosity is suggested and simulation results show that it can reach a higher discharge capacity without decreasing its power density. Detailed mass transport processes in the battery are also studied. - Highlights: • Electrolyte is circulated through the cathode and externally saturated with oxygen. • A two-dimensional, transient, non-isothermal model is developed for a Li–O 2 battery. • The new design's capacity can be 15.5 times that of a battery with passive cathode. • A cathode with non-uniform porosity is proposed to further enhance battery capacity

Analysis of model interfaces for Li ion batteries

Energy Technology Data Exchange (ETDEWEB)

Seemayer, Andreas; Pareek, Aparna; Vogel, Dirk; Rohwerder, Michael; Renner, Frank [Max-Planck-Institut fuer Eisenforschung GmbH, Duesseldorf (Germany)

2010-07-01

Lithium ion batteries are the most promising power source for future electromobility applications. Therefore a better understanding of the basic processes in Lithium ion batteries is needed. Especially nowadays research projects aim to improve real systems in terms of higher rate capability, cycle life, safety and operating temperature. Following the surface science approach we focus on the investigation of single crystal model systems of possible anode and cathode materials and electrode/solid electrolyte interfaces prepared by electrochemical deposition, molecular beam epitaxy or pulsed laser deposition.

Online Internal Temperature Estimation for Lithium-Ion Batteries Based on Kalman Filter

OpenAIRE

Jinlei Sun; Guo Wei; Lei Pei; Rengui Lu; Kai Song; Chao Wu; Chunbo Zhu

2015-01-01

The battery internal temperature estimation is important for the thermal safety in applications, because the internal temperature is hard to measure directly. In this work, an online internal temperature estimation method based on a simplified thermal model using a Kalman filter is proposed. As an improvement, the influences of entropy change and overpotential on heat generation are analyzed quantitatively. The model parameters are identified through a current pulse test. The charge/discharg...

An algorithm for management of deep brain stimulation battery replacements: devising a web-based battery estimator and clinical symptom approach.

Science.gov (United States)

Montuno, Michael A; Kohner, Andrew B; Foote, Kelly D; Okun, Michael S

2013-01-01

Deep brain stimulation (DBS) is an effective technique that has been utilized to treat advanced and medication-refractory movement and psychiatric disorders. In order to avoid implanted pulse generator (IPG) failure and consequent adverse symptoms, a better understanding of IPG battery longevity and management is necessary. Existing methods for battery estimation lack the specificity required for clinical incorporation. Technical challenges prevent higher accuracy longevity estimations, and a better approach to managing end of DBS battery life is needed. The literature was reviewed and DBS battery estimators were constructed by the authors and made available on the web at http://mdc.mbi.ufl.edu/surgery/dbs-battery-estimator. A clinical algorithm for management of DBS battery life was constructed. The algorithm takes into account battery estimations and clinical symptoms. Existing methods of DBS battery life estimation utilize an interpolation of averaged current drains to calculate how long a battery will last. Unfortunately, this technique can only provide general approximations. There are inherent errors in this technique, and these errors compound with each iteration of the battery estimation. Some of these errors cannot be accounted for in the estimation process, and some of the errors stem from device variation, battery voltage dependence, battery usage, battery chemistry, impedance fluctuations, interpolation error, usage patterns, and self-discharge. We present web-based battery estimators along with an algorithm for clinical management. We discuss the perils of using a battery estimator without taking into account the clinical picture. Future work will be needed to provide more reliable management of implanted device batteries; however, implementation of a clinical algorithm that accounts for both estimated battery life and for patient symptoms should improve the care of DBS patients. © 2012 International Neuromodulation Society.

Parallelized Genetic Identification of the Thermal-Electrochemical Model for Lithium-Ion Battery

Directory of Open Access Journals (Sweden)

Liqiang Zhang

2013-01-01

Full Text Available The parameters of a well predicted model can be used as health characteristics for Lithium-ion battery. This article reports a parallelized parameter identification of the thermal-electrochemical model, which significantly reduces the time consumption of parameter identification. Since the P2D model has the most predictability, it is chosen for further research and expanded to the thermal-electrochemical model by coupling thermal effect and temperature-dependent parameters. Then Genetic Algorithm is used for parameter identification, but it takes too much time because of the long time simulation of model. For this reason, a computer cluster is built by surplus computing resource in our laboratory based on Parallel Computing Toolbox and Distributed Computing Server in MATLAB. The performance of two parallelized methods, namely Single Program Multiple Data (SPMD and parallel FOR loop (PARFOR, is investigated and then the parallelized GA identification is proposed. With this method, model simulations running parallelly and the parameter identification could be speeded up more than a dozen times, and the identification result is batter than that from serial GA. This conclusion is validated by model parameter identification of a real LiFePO4 battery.

Performance Modeling of a Vanadium Redox Flow Battery during Discharging

International Nuclear Information System (INIS)

Yang, W.W.; He, Y.L.; Li, Y.S.

2015-01-01

A two-dimensional quasi-steady-state model is presented to simulate coupled mass-species-charge transfer and electrochemical reactions in all vanadium redox flow battery. Emphasis is located on examining the influences of applied current density, initial vanadium concentration, initial acid concentration and electrolyte flow rate on overpotentials in both electrodes, ohmic loss in electrolyte phase as well as battery discharging voltage. It is indicated that overpotential in negative electrode is the dominant factor causing the loss of battery discharging voltage at relatively lower or higher state of charge, while ohmic loss in electrolyte phase is dominant when discharging at moderate state of charge. Increasing initial vanadium concentration, the battery discharging voltage is significantly increased due to the reduced overpotentials in both electrodes. With the increase in initial acid concentration, the battery discharging voltage is also obviously increased because of increased open circuit voltage and decreased ohmic loss in electrolyte phase. As the electrolyte flow rate increases, the total discharging time is extended due to the retarded concentration polarization and the battery discharging voltage is obviously increased at lower state of charge

Evaluation of Lithium-Ion Battery Equivalent Circuit Models for State of Charge Estimation by an Experimental Approach

Directory of Open Access Journals (Sweden)

Jinxin Fan

2011-03-01

Full Text Available To improve the use of lithium-ion batteries in electric vehicle (EV applications, evaluations and comparisons of different equivalent circuit models are presented in this paper. Based on an analysis of the traditional lithium-ion battery equivalent circuit models such as the Rint, RC, Thevenin and PNGV models, an improved Thevenin model, named dual polarization (DP model, is put forward by adding an extra RC to simulate the electrochemical polarization and concentration polarization separately. The model parameters are identified with a genetic algorithm, which is used to find the optimal time constant of the model, and the experimental data from a Hybrid Pulse Power Characterization (HPPC test on a LiMn2O4 battery module. Evaluations on the five models are carried out from the point of view of the dynamic performance and the state of charge (SoC estimation. The dynamic performances of the five models are obtained by conducting the Dynamic Stress Test (DST and the accuracy of SoC estimation with the Robust Extended Kalman Filter (REKF approach is determined by performing a Federal Urban Driving Schedules (FUDS experiment. By comparison, the DP model has the best dynamic performance and provides the most accurate SoC estimation. Finally, sensitivity of the different SoC initial values is investigated based on the accuracy of SoC estimation with the REKF approach based on the DP model. It is clear that the errors resulting from the SoC initial value are significantly reduced and the true SoC is convergent within an acceptable error.

Battery Internal Temperature Estimation for LiFePO4 Battery Based on Impedance Phase Shift under Operating Conditions

Directory of Open Access Journals (Sweden)

Jiangong Zhu

2017-01-01

Full Text Available An impedance-based temperature estimation method is investigated considering the electrochemical non-equilibrium with short-term relaxation time for facilitating the vehicular application. Generally, sufficient relaxation time is required for battery electrochemical equilibrium before the impedance measurement. A detailed experiment is performed to investigate the regularity of the battery impedance in short-term relaxation time after switch-off current excitation, which indicates that the impedance can be measured and also has systematical decrement with the relaxation time growth. Based on the discussion of impedance variation in electrochemical perspective, as well as the monotonic relationship between impedance phase shift and battery internal temperature in the electrochemical equilibrium state, an exponential equation that accounts for both measured phase shift and relaxation time is established to correct the measuring deviation caused by electrochemical non-equilibrium. Then, a multivariate linear equation coupled with ambient temperature is derived considering the temperature gradients between the active part and battery surface. Equations stated above are all identified with the embedded thermocouple experimentally. In conclusion, the temperature estimation method can be a valuable alternative for temperature monitoring during cell operating, and serve the functionality as an efficient implementation in battery thermal management system for electric vehicles (EVs and hybrid electric vehicles (HEVs.

Robust Online State of Charge Estimation of Lithium-Ion Battery Pack Based on Error Sensitivity Analysis

Directory of Open Access Journals (Sweden)

Ting Zhao

2015-01-01

Full Text Available Accurate and reliable state of charge (SOC estimation is a key enabling technique for large format lithium-ion battery pack due to its vital role in battery safety and effective management. This paper tries to make three contributions to existing literatures through robust algorithms. (1 Observer based SOC estimation error model is established, where the crucial parameters on SOC estimation accuracy are determined by quantitative analysis, being a basis for parameters update. (2 The estimation method for a battery pack in which the inconsistency of cells is taken into consideration is proposed, ensuring all batteries’ SOC ranging from 0 to 1, effectively avoiding the battery overcharged/overdischarged. Online estimation of the parameters is also presented in this paper. (3 The SOC estimation accuracy of the battery pack is verified using the hardware-in-loop simulation platform. The experimental results at various dynamic test conditions, temperatures, and initial SOC difference between two cells demonstrate the efficacy of the proposed method.

An electro-thermal model and its application on a spiral-wound lithium ion battery with porous current collectors

International Nuclear Information System (INIS)

Ye, Yonghuang; Shi, Yixiang; Saw, Lip Huat; Tay, Andrew A.O.

2014-01-01

Highlights: • A local electro-thermal model is developed to verify the validity of a lump electro-thermal model. • Comparisons on edge effect of batteries with porous current collectors and batteries normal current collector foil. • Investigation on thermal performance of novel battery with porous current collector sheets. - Abstract: A local electro-thermal model for a spiral-wound lithium ion battery is developed to provide detailed and local insights of electrochemistry, transport phenomenon and heat transfer processes in spiral-wound geometries. The discharging potential, bulk heat generation rate, battery surface temperature and the temperature distribution within battery predicted by the model are used to verify a lumped electro-thermal model. The results show good agreement between the lumped electro-thermal model and the local electro-thermal model. The edge effect is investigated using the local electro-thermal model. And the results indicate that a novel battery with porous current collector sheets has a higher utilization rate of porous electrode materials than a commercial battery with normal current collector foils. The novel battery with porous current collector sheets is also investigated using the local electro-thermal model, simulation results show smaller liquid phase potential gradient and smaller liquid concentration gradient in the novel battery. The increased electrical resistance has minor effect on the overall heat generation within the battery when the porous current collector is employed, while it reduces the discharging potential of the battery

Polyanthraquinone-Based Organic Cathode for High-Performance Rechargeable Magnesium-Ion Batteries

Energy Technology Data Exchange (ETDEWEB)

Pan, Baofei [Joint Center for Energy Storage Research, Chemical Science and Engineering Division, Argonne National Laboratory, Lemont IL 60439 USA; Huang, Jinhua [Joint Center for Energy Storage Research, Chemical Science and Engineering Division, Argonne National Laboratory, Lemont IL 60439 USA; Feng, Zhenxing [Joint Center for Energy Storage Research, Chemical Science and Engineering Division, Argonne National Laboratory, Lemont IL 60439 USA; Zeng, Li [Applied Physics Program, Department of Materials Science and Engineering and Department of Physics and Astronomy, Northwestern University, Evanston IL 60208 USA; He, Meinan [Joint Center for Energy Storage Research, Chemical Science and Engineering Division, Argonne National Laboratory, Lemont IL 60439 USA; Zhang, Lu [Joint Center for Energy Storage Research, Chemical Science and Engineering Division, Argonne National Laboratory, Lemont IL 60439 USA; Vaughey, John T. [Joint Center for Energy Storage Research, Chemical Science and Engineering Division, Argonne National Laboratory, Lemont IL 60439 USA; Bedzyk, Michael J. [Applied Physics Program, Department of Materials Science and Engineering and Department of Physics and Astronomy, Northwestern University, Evanston IL 60208 USA; Fenter, Paul [Joint Center for Energy Storage Research, Chemical Science and Engineering Division, Argonne National Laboratory, Lemont IL 60439 USA; Zhang, Zhengcheng [Joint Center for Energy Storage Research, Chemical Science and Engineering Division, Argonne National Laboratory, Lemont IL 60439 USA; Burrell, Anthony K. [Joint Center for Energy Storage Research, Chemical Science and Engineering Division, Argonne National Laboratory, Lemont IL 60439 USA; Liao, Chen [Joint Center for Energy Storage Research, Chemical Science and Engineering Division, Argonne National Laboratory, Lemont IL 60439 USA

2016-05-09

Two anthraquinone-based polymers aiming at improving the capacity and voltage of magnesium ion batteries, were synthesized and characterized. The excellent battery cycling performance was demonstrated with the electrolyte consisting of magnesium bis(hexamethyldisilazide) and magnesium chloride.

Can innovative business models overcome resistance to electric vehicles? Better Place and battery electric cars in Denmark

International Nuclear Information System (INIS)

Budde Christensen, Thomas; Wells, Peter; Cipcigan, Liana

2012-01-01

This paper explores the geographical and policy context for an emergent business model from Better Place to deliver battery electric car mobility in Denmark. It argues that the combination of radically different technologies and a highly complex multi-agency operating environment theoretically provide the conditions and requirements for such an emergent business model. While focused on battery electric cars, renewable energy generation and smart grids, the paper has wider applicability to an understanding of the interplay between place, innovation and sustainability which suggests that diverse solutions are likely to be the characteristic solution rather than ubiquity and standardization. The paper argues, however, that the innovative business model, the deployment of electric vehicles, and the use of renewable energy systems, in this case largely based on wind power, while mutually supportive and contributing to wider policy aims with respect to the reduction of carbon emissions, may still fail in the face of entrenched practices. At the theoretical level it is concluded that theorization of business models needs a broader perspective beyond the typical ‘value creation, value capture’ rubric to better understand the wider role such models have in meeting societal goals, and to understand the structural impediments to organizational and technical innovation. - Highlights: ► We explore the context for an innovative emergent business model to deliver battery electric car mobility in Denmark. ► We explore the interplay between battery electric cars, renewable energy generation and smart grids. ► We discuss the integration of electric cars in energy systems based on renewable energy sources. ► We discuss the likely success of the Better Place business model.

76 FR 41142 - Special Conditions; Cessna Aircraft Company Model M680 Airplane; Lithium-ion Battery Installations

Science.gov (United States)

2011-07-13

... Company Model M680 Airplane; Lithium-ion Battery Installations AGENCY: Federal Aviation Administration... design feature associated with Lithium-ion batteries. The applicable airworthiness regulations do not...) T00012WI for installation of Lithium-ion batteries in the Model 680. The Model 680 is a twin-engine, medium...

Recent Progress in the Design of Advanced Cathode Materials and Battery Models for High-Performance Lithium-X (X = O2 , S, Se, Te, I2 , Br2 ) Batteries.

Science.gov (United States)

Xu, Jiantie; Ma, Jianmin; Fan, Qinghua; Guo, Shaojun; Dou, Shixue

2017-07-01

Recent advances and achievements in emerging Li-X (X = O 2 , S, Se, Te, I 2 , Br 2 ) batteries with promising cathode materials open up new opportunities for the development of high-performance lithium-ion battery alternatives. In this review, we focus on an overview of recent important progress in the design of advanced cathode materials and battery models for developing high-performance Li-X (X = O 2 , S, Se, Te, I 2 , Br 2 ) batteries. We start with a brief introduction to explain why Li-X batteries are important for future renewable energy devices. Then, we summarize the existing drawbacks, major progress and emerging challenges in the development of cathode materials for Li-O 2 (S) batteries. In terms of the emerging Li-X (Se, Te, I 2 , Br 2 ) batteries, we systematically summarize their advantages/disadvantages and recent progress. Specifically, we review the electrochemical performance of Li-Se (Te) batteries using carbonate-/ether-based electrolytes, made with different electrode fabrication techniques, and of Li-I 2 (Br 2 ) batteries with various cell designs (e.g., dual electrolyte, all-organic electrolyte, with/without cathode-flow mode, and fuel cell/solar cell integration). Finally, the perspective on and challenges for the development of cathode materials for the promising Li-X (X = O 2 , S, Se, Te, I 2 , Br 2 ) batteries is presented. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Review of Parameter Determination for Thermal Modeling of Lithium Ion Batteries

DEFF Research Database (Denmark)

Saeed Madani, Seyed; Schaltz, Erik; Kær, Søren Knudsen

2018-01-01

This paper reviews different methods for determination of thermal parameters of lithium ion batteries. Lithium ion batteries are extensively employed for various applications owing to their low memory effect, high specific energy, and power density. One of the problems in the expansion of hybrid...... on the lifetime of lithium ion battery cells. Thermal management is critical in electric vehicles (EVs) and good thermal battery models are necessary to design proper heating and cooling systems. Consequently, it is necessary to determine thermal parameters of a single cell, such as internal resistance, specific...... and electric vehicle technology is the management and control of operation temperatures and heat generation. Successful battery thermal management designs can lead to better reliability and performance of hybrid and electric vehicles. Thermal cycling and temperature gradients could have a considerable impact...

Control oriented 1D electrochemical model of lithium ion battery

International Nuclear Information System (INIS)

Smith, Kandler A.; Rahn, Christopher D.; Wang, Chao-Yang

2007-01-01

Lithium ion (Li-ion) batteries provide high energy and power density energy storage for diverse applications ranging from cell phones to hybrid electric vehicles (HEVs). For efficient and reliable systems integration, low order dynamic battery models are needed. This paper introduces a general method to generate numerically a fully observable/controllable state variable model from electrochemical kinetic, species and charge partial differential equations that govern the discharge/charge behavior of a Li-ion battery. Validated against a 313th order nonlinear CFD model of a 6 Ah HEV cell, a 12th order state variable model predicts terminal voltage to within 1% for pulse and constant current profiles at rates up to 50 C. The state equation is constructed in modal form with constant negative real eigenvalues distributed in frequency space from 0 to 10 Hz. Open circuit potential, electrode surface concentration/reaction distribution coupling and electrolyte concentration/ionic conductivity nonlinearities are explicitly approximated in the model output equation on a local, electrode-averaged and distributed basis, respectively. The balanced realization controllability/observability gramian indicates that the fast electrode surface concentration dynamics are more observable/controllable than the electrode bulk concentration dynamics (i.e. state of charge)

Online Identification with Reliability Criterion and State of Charge Estimation Based on a Fuzzy Adaptive Extended Kalman Filter for Lithium-Ion Batteries

Directory of Open Access Journals (Sweden)

Zhongwei Deng

2016-06-01

Full Text Available In the field of state of charge (SOC estimation, the Kalman filter has been widely used for many years, although its performance strongly depends on the accuracy of the battery model as well as the noise covariance. The Kalman gain determines the confidence coefficient of the battery model by adjusting the weight of open circuit voltage (OCV correction, and has a strong correlation with the measurement noise covariance (R. In this paper, the online identification method is applied to acquire the real model parameters under different operation conditions. A criterion based on the OCV error is proposed to evaluate the reliability of online parameters. Besides, the equivalent circuit model produces an intrinsic model error which is dependent on the load current, and the property that a high battery current or a large current change induces a large model error can be observed. Based on the above prior knowledge, a fuzzy model is established to compensate the model error through updating R. Combining the positive strategy (i.e., online identification and negative strategy (i.e., fuzzy model, a more reliable and robust SOC estimation algorithm is proposed. The experiment results verify the proposed reliability criterion and SOC estimation method under various conditions for LiFePO4 batteries.

Stand Alone Battery Thermal Management System

Energy Technology Data Exchange (ETDEWEB)

Brodie, Brad [Denso International America, Incorporated, Southfield, MI (United States)

2015-09-30

The objective of this project is research, development and demonstration of innovative thermal management concepts that reduce the cell or battery weight, complexity (component count) and/or cost by at least 20%. The project addresses two issues that are common problems with current state of the art lithium ion battery packs used in vehicles; low power at cold temperatures and reduced battery life when exposed to high temperatures. Typically, battery packs are “oversized” to satisfy the two issues mentioned above. The first phase of the project was spent making a battery pack simulation model using AMEsim software. The battery pack used as a benchmark was from the Fiat 500EV. FCA and NREL provided vehicle data and cell data that allowed an accurate model to be created that matched the electrical and thermal characteristics of the actual battery pack. The second phase involved using the battery model from the first phase and evaluate different thermal management concepts. In the end, a gas injection heat pump system was chosen as the dedicated thermal system to both heat and cool the battery pack. Based on the simulation model. The heat pump system could use 50% less energy to heat the battery pack in -20°C ambient conditions, and by keeping the battery cooler at hot climates, the battery pack size could be reduced by 5% and still meet the warranty requirements. During the final phase, the actual battery pack and heat pump system were installed in a test bench at DENSO to validate the simulation results. Also during this phase, the system was moved to NREL where testing was also done to validate the results. In conclusion, the heat pump system can improve “fuel economy” (for electric vehicle) by 12% average in cold climates. Also, the battery pack size, or capacity, could be reduced 5%, or if pack size is kept constant, the pack life could be increased by two years. Finally, the total battery pack and thermal system cost could be reduced 5% only if the

A phenomenological force model of Li-ion battery packs for enhanced performance and health management

Science.gov (United States)

Oh, Ki-Yong; Epureanu, Bogdan I.

2017-10-01

A 1-D phenomenological force model of a Li-ion battery pack is proposed to enhance the control performance of Li-ion battery cells in pack conditions for efficient performance and health management. The force model accounts for multiple swelling sources under the operational environment of electric vehicles to predict swelling-induced forces in pack conditions, i.e. mechanically constrained. The proposed force model not only incorporates structural nonlinearities due to Li-ion intercalation swelling, but also separates the overall range of states of charge into three ranges to account for phase transitions. Moreover, an approach to study cell-to-cell variations in pack conditions is proposed with serial and parallel combinations of linear and nonlinear stiffness, which account for battery cells and other components in the battery pack. The model is shown not only to accurately estimate the reaction force caused by swelling as a function of the state of charge, battery temperature and environmental temperature, but also to account for cell-to-cell variations due to temperature variations, SOC differences, and local degradation in a wide range of operational conditions of electric vehicles. Considering that the force model of Li-ion battery packs can account for many possible situations in actual operation, the proposed approach and model offer potential utility for the enhancement of current battery management systems and power management strategies.

Data-driven method based on particle swarm optimization and k-nearest neighbor regression for estimating capacity of lithium-ion battery

International Nuclear Information System (INIS)

Hu, Chao; Jain, Gaurav; Zhang, Puqiang; Schmidt, Craig; Gomadam, Parthasarathy; Gorka, Tom

2014-01-01

Highlights: • We develop a data-driven method for the battery capacity estimation. • Five charge-related features that are indicative of the capacity are defined. • The kNN regression model captures the dependency of the capacity on the features. • Results with 10 years’ continuous cycling data verify the effectiveness of the method. - Abstract: Reliability of lithium-ion (Li-ion) rechargeable batteries used in implantable medical devices has been recognized as of high importance from a broad range of stakeholders, including medical device manufacturers, regulatory agencies, physicians, and patients. To ensure Li-ion batteries in these devices operate reliably, it is important to be able to assess the battery health condition by estimating the battery capacity over the life-time. This paper presents a data-driven method for estimating the capacity of Li-ion battery based on the charge voltage and current curves. The contributions of this paper are three-fold: (i) the definition of five characteristic features of the charge curves that are indicative of the capacity, (ii) the development of a non-linear kernel regression model, based on the k-nearest neighbor (kNN) regression, that captures the complex dependency of the capacity on the five features, and (iii) the adaptation of particle swarm optimization (PSO) to finding the optimal combination of feature weights for creating a kNN regression model that minimizes the cross validation (CV) error in the capacity estimation. Verification with 10 years’ continuous cycling data suggests that the proposed method is able to accurately estimate the capacity of Li-ion battery throughout the whole life-time

Numerical studies of carbon paper-based vanadium redox flow batteries

International Nuclear Information System (INIS)

Won, Seongyeon; Oh, Kyeongmin; Ju, Hyunchul

2016-01-01

ABSTRACT: This study analyzed theoretically the effects of a carbon paper (CP)-based electrode on the performance of a vanadium redox flow battery (VRFB). Compared to conventional carbon felt-based electrode materials, the CP-based electrode showed superior characteristics in facilitating the redox reactions of VO"2"+/VO_2"+ and V"2"+/V"3"+ couples, such as better electrochemical activity and higher electronic conductivity. A three-dimensional, non-isothermal VRFB model developed in a previous study was applied to a range of single cell structures equipped with CP-based electrodes and flow channels in the current collectors. The model was then validated using the experimental data measured under the CP- and channel-based VRFB geometries. The model successfully captured the experimental trend that showed a higher discharging performance with increasing number of CP layers used for each electrode. The simulation results clearly showed that the activation overpotentials in the electrodes were reduced significantly using more CP layers, which dominated over the effects of increased mass transport limitation of vanadium ions due to the thicker electrode.

Poly(vinylidene fluoride-hexafluoropropylene polymer electrolyte for paper-based and flexible battery applications

Directory of Open Access Journals (Sweden)

Nojan Aliahmad

2016-06-01

Full Text Available Paper-based batteries represent a new frontier in battery technology. However, low-flexibility and poor ionic conductivity of solid electrolytes have been major impediments in achieving practical mechanically flexible batteries. This work discuss new highly ionic conductive polymer gel electrolytes for paper-based battery applications. In this paper, we present a poly(vinylidene fluoride-hexafluoropropylene (PVDH-HFP porous membrane electrolyte enhanced with lithium bis(trifluoromethane sulphoneimide (LiTFSI and lithium aluminum titanium phosphate (LATP, with an ionic conductivity of 2.1 × 10−3 S cm−1. Combining ceramic (LATP with the gel structure of PVDF-HFP and LiTFSI ionic liquid harnesses benefits of ceramic and gel electrolytes in providing flexible electrolytes with a high ionic conductivity. In a flexibility test experiment, bending the polymer electrolyte at 90° for 20 times resulted in 14% decrease in ionic conductivity. Efforts to further improving the flexibility of the presented electrolyte are ongoing. Using this electrolyte, full-cell batteries with lithium titanium oxide (LTO and lithium cobalt oxide (LCO electrodes and (i standard metallic current collectors and (ii paper-based current collectors were fabricated and tested. The achieved specific capacities were (i 123 mAh g−1 for standard metallic current collectors and (ii 99.5 mAh g−1 for paper-based current collectors. Thus, the presented electrolyte has potential to become a viable candidate in paper-based and flexible battery applications. Fabrication methods, experimental procedures, and test results for the polymer gel electrolyte and batteries are presented and discussed.

Poly(vinylidene fluoride-hexafluoropropylene) polymer electrolyte for paper-based and flexible battery applications

Science.gov (United States)

Aliahmad, Nojan; Shrestha, Sudhir; Varahramyan, Kody; Agarwal, Mangilal

2016-06-01

Paper-based batteries represent a new frontier in battery technology. However, low-flexibility and poor ionic conductivity of solid electrolytes have been major impediments in achieving practical mechanically flexible batteries. This work discuss new highly ionic conductive polymer gel electrolytes for paper-based battery applications. In this paper, we present a poly(vinylidene fluoride-hexafluoropropylene) (PVDH-HFP) porous membrane electrolyte enhanced with lithium bis(trifluoromethane sulphone)imide (LiTFSI) and lithium aluminum titanium phosphate (LATP), with an ionic conductivity of 2.1 × 10-3 S cm-1. Combining ceramic (LATP) with the gel structure of PVDF-HFP and LiTFSI ionic liquid harnesses benefits of ceramic and gel electrolytes in providing flexible electrolytes with a high ionic conductivity. In a flexibility test experiment, bending the polymer electrolyte at 90° for 20 times resulted in 14% decrease in ionic conductivity. Efforts to further improving the flexibility of the presented electrolyte are ongoing. Using this electrolyte, full-cell batteries with lithium titanium oxide (LTO) and lithium cobalt oxide (LCO) electrodes and (i) standard metallic current collectors and (ii) paper-based current collectors were fabricated and tested. The achieved specific capacities were (i) 123 mAh g-1 for standard metallic current collectors and (ii) 99.5 mAh g-1 for paper-based current collectors. Thus, the presented electrolyte has potential to become a viable candidate in paper-based and flexible battery applications. Fabrication methods, experimental procedures, and test results for the polymer gel electrolyte and batteries are presented and discussed.

Poly(vinylidene fluoride-hexafluoropropylene) polymer electrolyte for paper-based and flexible battery applications

Energy Technology Data Exchange (ETDEWEB)

Aliahmad, Nojan; Shrestha, Sudhir; Varahramyan, Kody [Department of Electrical & Computer Engineering, Indiana University-Purdue University Indianapolis (IUPUI), Indianapolis, IN, 46202 (United States); Integrated Nanosystems Development Institute (INDI), Indiana University-Purdue University Indianapolis (IUPUI), Indianapolis, IN, 46202 (United States); Agarwal, Mangilal, E-mail: agarwal@iupui.edu [Department of Electrical & Computer Engineering, Indiana University-Purdue University Indianapolis (IUPUI), Indianapolis, IN, 46202 (United States); Integrated Nanosystems Development Institute (INDI), Indiana University-Purdue University Indianapolis (IUPUI), Indianapolis, IN, 46202 (United States); Department of Mechanical Engineering, Indiana University-Purdue University Indianapolis (IUPUI), Indianapolis, IN, 46202 (United States)

2016-06-15

Paper-based batteries represent a new frontier in battery technology. However, low-flexibility and poor ionic conductivity of solid electrolytes have been major impediments in achieving practical mechanically flexible batteries. This work discuss new highly ionic conductive polymer gel electrolytes for paper-based battery applications. In this paper, we present a poly(vinylidene fluoride-hexafluoropropylene) (PVDH-HFP) porous membrane electrolyte enhanced with lithium bis(trifluoromethane sulphone)imide (LiTFSI) and lithium aluminum titanium phosphate (LATP), with an ionic conductivity of 2.1 × 10{sup −3} S cm{sup −1}. Combining ceramic (LATP) with the gel structure of PVDF-HFP and LiTFSI ionic liquid harnesses benefits of ceramic and gel electrolytes in providing flexible electrolytes with a high ionic conductivity. In a flexibility test experiment, bending the polymer electrolyte at 90° for 20 times resulted in 14% decrease in ionic conductivity. Efforts to further improving the flexibility of the presented electrolyte are ongoing. Using this electrolyte, full-cell batteries with lithium titanium oxide (LTO) and lithium cobalt oxide (LCO) electrodes and (i) standard metallic current collectors and (ii) paper-based current collectors were fabricated and tested. The achieved specific capacities were (i) 123 mAh g{sup −1} for standard metallic current collectors and (ii) 99.5 mAh g{sup −1} for paper-based current collectors. Thus, the presented electrolyte has potential to become a viable candidate in paper-based and flexible battery applications. Fabrication methods, experimental procedures, and test results for the polymer gel electrolyte and batteries are presented and discussed.

A Comparative Study Based on the Least Square Parameter Identification Method for State of Charge Estimation of a LiFePO4 Battery Pack Using Three Model-Based Algorithms for Electric Vehicles

Directory of Open Access Journals (Sweden)

Taimoor Zahid

2016-09-01

Full Text Available Battery energy storage management for electric vehicles (EV and hybrid EV is the most critical and enabling technology since the dawn of electric vehicle commercialization. A battery system is a complex electrochemical phenomenon whose performance degrades with age and the existence of varying material design. Moreover, it is very tedious and computationally very complex to monitor and control the internal state of a battery’s electrochemical systems. For Thevenin battery model we established a state-space model which had the advantage of simplicity and could be easily implemented and then applied the least square method to identify the battery model parameters. However, accurate state of charge (SoC estimation of a battery, which depends not only on the battery model but also on highly accurate and efficient algorithms, is considered one of the most vital and critical issue for the energy management and power distribution control of EV. In this paper three different estimation methods, i.e., extended Kalman filter (EKF, particle filter (PF and unscented Kalman Filter (UKF, are presented to estimate the SoC of LiFePO4 batteries for an electric vehicle. Battery’s experimental data, current and voltage, are analyzed to identify the Thevenin equivalent model parameters. Using different open circuit voltages the SoC is estimated and compared with respect to the estimation accuracy and initialization error recovery. The experimental results showed that these online SoC estimation methods in combination with different open circuit voltage-state of charge (OCV-SoC curves can effectively limit the error, thus guaranteeing the accuracy and robustness.

Range-extending Zinc-air battery for electric vehicle

Directory of Open Access Journals (Sweden)

Steven B. Sherman

2018-01-01

Full Text Available A vehicle model is used to evaluate a novel powertrain that is comprised of a dual energy storage system (Dual ESS. The system includes two battery packs with different chemistries and the necessary electronic controls to facilitate their coordination and optimization. Here, a lithium-ion battery pack is used as the primary pack and a Zinc-air battery as the secondary or range-extending pack. Zinc-air batteries are usually considered unsuitable for use in vehicles due to their poor cycle life, but the model demonstrates the feasibility of this technology with an appropriate control strategy, with limited cycling of the range extender pack. The battery pack sizes and the battery control strategy are configured to optimize range, cost and longevity. In simulation the vehicle performance compares favourably to a similar vehicle with a single energy storage system (Single ESS powertrain, travelling up to 75 km further under test conditions. The simulation demonstrates that the Zinc-air battery pack need only cycle 100 times to enjoy a ten-year lifespan. The Zinc-air battery model is based on leading Zinc-air battery research from literature, with some assumptions regarding achievable improvements. Having such a model clarifies the performance requirements of Zinc-air cells and improves the research community's ability to set performance targets for Zinc-air cells.

Real-time monitoring of capacity loss for vanadium redox flow battery

Science.gov (United States)

Wei, Zhongbao; Bhattarai, Arjun; Zou, Changfu; Meng, Shujuan; Lim, Tuti Mariana; Skyllas-Kazacos, Maria

2018-06-01

The long-term operation of the vanadium redox flow battery is accompanied by ion diffusion across the separator and side reactions, which can lead to electrolyte imbalance and capacity loss. The accurate online monitoring of capacity loss is therefore valuable for the reliable and efficient operation of vanadium redox flow battery system. In this paper, a model-based online monitoring method is proposed to detect capacity loss in the vanadium redox flow battery in real time. A first-order equivalent circuit model is built to capture the dynamics of the vanadium redox flow battery. The model parameters are online identified from the onboard measureable signals with the recursive least squares, in seeking to keep a high modeling accuracy and robustness under a wide range of working scenarios. Based on the online adapted model, an observer is designed with the extended Kalman Filter to keep tracking both the capacity and state of charge of the battery in real time. Experiments are conducted on a lab-scale battery system. Results suggest that the online adapted model is able to simulate the battery behavior with high accuracy. The capacity loss as well as the state of charge can be estimated accurately in a real-time manner.

Analysis and Modeling of Heat Generation in Overcharged Li-Ion Battery with Passive Cooling

DEFF Research Database (Denmark)

Coman, Paul Tiberiu; Veje, Christian

2013-01-01

This paper presents a dynamic model for simulating the heat generation in Lithium batteries and an investigation of the heat transfer as well as the capacity of Phase Change Materials (PCM’s) to store energy inside a battery cell module when the battery is overcharged. The study is performed...... by coupling a one-dimensional model of the electrochemical processes with a two-dimensional model for the heat transfer in a cross section of a battery pack. The heat generation and subsequent temperature rise is analyzed for different charging currents for the two cases where the cell is air......-cooled and passively cooled using a PCM, respectively. As expected, the results show that for high currents, the heat generation and implicitly the temperature increases. However, using a PCM the temperature increase is found to be limited allowing the battery to be overcharged to a certain degree. It is found...

Mathematical Model of a Lithium/Thionyl Chloride Battery

Energy Technology Data Exchange (ETDEWEB)

Jain, M.; Jungst, R.G.; Nagasubramanian, G.; Weidner, J.W.

1998-11-24

A mathematical model of a spirally wound lithium/thionyl chloride primary battery has been developed ~d used for parameter estimation and design studies. The model formulation is based on the fimdarnental Consemation laws using porous electrode theory and concentrated solution theory. The model is used to estimate the difision coefficient and the kinetic parameters for the reactions at the anode and the cathode as a function of temperature. These parameters are obtained by fitting the simulated capacity and average cell voltage to experimental data over a wide range of temperatures (-55 to 49"C) and discharge loads (10 to 250 ohms). The experiments were performed on D-sized, cathode-limited, spirally wound lithium/thionyl chloride cells. The model is also used to study the effkct of cathode thickness on the cell capacity as a finction of temperature, and it was found that the optimum thickness for the cathode- limited design is temperature and load dependent.

Lithium-Based High Energy Density Flow Batteries

Science.gov (United States)

Bugga, Ratnakumar V. (Inventor); West, William C. (Inventor); Kindler, Andrew (Inventor); Smart, Marshall C. (Inventor)

2014-01-01

Systems and methods in accordance with embodiments of the invention implement a lithium-based high energy density flow battery. In one embodiment, a lithium-based high energy density flow battery includes a first anodic conductive solution that includes a lithium polyaromatic hydrocarbon complex dissolved in a solvent, a second cathodic conductive solution that includes a cathodic complex dissolved in a solvent, a solid lithium ion conductor disposed so as to separate the first solution from the second solution, such that the first conductive solution, the second conductive solution, and the solid lithium ionic conductor define a circuit, where when the circuit is closed, lithium from the lithium polyaromatic hydrocarbon complex in the first conductive solution dissociates from the lithium polyaromatic hydrocarbon complex, migrates through the solid lithium ionic conductor, and associates with the cathodic complex of the second conductive solution, and a current is generated.

Microcapsule-based techniques for improving the safety of lithium-ion batteries

Science.gov (United States)

Baginska, Marta

Lithium-ion batteries are vital energy storage devices due to their high specific energy density, lack of memory effect, and long cycle life. While they are predominantly used in small consumer electronics, new strategies for improving battery safety and lifetime are critical to the successful implementation of high-capacity, fast-charging materials required for advanced Li-ion battery applications. Currently, the presence of a volatile, combustible electrolyte and an oxidizing agent (Lithium oxide cathodes) make the Li-ion cell susceptible to fire and explosions. Thermal overheating, electrical overcharging, or mechanical damage can trigger thermal runaway, and if left unchecked, combustion of battery materials. To improve battery safety, autonomic, thermally-induced shutdown of Li-ion batteries is demonstrated by depositing thermoresponsive polymer microspheres onto battery anodes. When the internal temperature of the cell reaches a critical value, the microspheres melt and conformally coat the anode and/or separator with an ion insulating barrier, halting Li-ion transport and shutting down the cell permanently. Charge and discharge capacity is measured for Li-ion coin cells containing microsphere-coated anodes or separators as a function of capsule coverage. Scanning electron microscopy images of electrode surfaces from cells that have undergone autonomic shutdown provides evidence of melting, wetting, and re-solidification of polyethylene (PE) into the anode and polymer film formation at the anode/separator interface. As an extension of this autonomic shutdown approach, a particle-based separator capable of performing autonomic shutdown, but which reduces the shorting hazard posed by current bi- and tri-polymer commercial separators, is presented. This dual-particle separator is composed of hollow glass microspheres acting as a physical spacer between electrodes, and PE microspheres to impart autonomic shutdown functionality. An oil-immersion technique is

Human Performance Task Batteries and Models: An Abilities-Based Directory

Science.gov (United States)

1986-12-01

8217. BATTERY/TASKLS^ f^ODELYS^ none located to date Sanders Stamina The ability to withstand considerable physical exertion without becoming winded or...Tha Frnfi Pmsg I Jerison, H.J. & Arginteau, J. (1958). Time judgment, acoustic noise and judgement drift (Technical Report No. 57-474). Dayton, OH

Heat input control in coke ovens battery using artificial intelligence

Energy Technology Data Exchange (ETDEWEB)

Kumar, R.; Kannan, C.; Sistla, S.; Kumar, D. [Tata Steel, Jamshedpur (India)

2005-07-01

Controlled heating is very essential for producing coke with certain desired properties. Controlled heating involves controlling the heat input into the battery dynamically depending on the various process parameters like current battery temperature, the set point of battery temperature, moisture in coal, ambient temperature, coal fineness, cake breakage etc. An artificial intelligence (AI) based heat input control has been developed in which currently some of the above mentioned process parameters are considered and used for calculating the pause time which is applied between reversal during the heating process. The AI based model currently considers 3 input variables, temperature deviation history, current deviation of the battery temperature from the target temperature and the actual heat input into the battery. Work is in progress to control the standard deviation of coke end temperature using this model. The new system which has been developed in-house has replaced Hoogovens supplied model. 7 figs.

A review of fractional-order techniques applied to lithium-ion batteries, lead-acid batteries, and supercapacitors

Science.gov (United States)

Zou, Changfu; Zhang, Lei; Hu, Xiaosong; Wang, Zhenpo; Wik, Torsten; Pecht, Michael

2018-06-01

Electrochemical energy storage systems play an important role in diverse applications, such as electrified transportation and integration of renewable energy with the electrical grid. To facilitate model-based management for extracting full system potentials, proper mathematical models are imperative. Due to extra degrees of freedom brought by differentiation derivatives, fractional-order models may be able to better describe the dynamic behaviors of electrochemical systems. This paper provides a critical overview of fractional-order techniques for managing lithium-ion batteries, lead-acid batteries, and supercapacitors. Starting with the basic concepts and technical tools from fractional-order calculus, the modeling principles for these energy systems are presented by identifying disperse dynamic processes and using electrochemical impedance spectroscopy. Available battery/supercapacitor models are comprehensively reviewed, and the advantages of fractional types are discussed. Two case studies demonstrate the accuracy and computational efficiency of fractional-order models. These models offer 15-30% higher accuracy than their integer-order analogues, but have reasonable complexity. Consequently, fractional-order models can be good candidates for the development of advanced battery/supercapacitor management systems. Finally, the main technical challenges facing electrochemical energy storage system modeling, state estimation, and control in the fractional-order domain, as well as future research directions, are highlighted.

Battery Ownership Model - Medium Duty HEV Battery Leasing & Standardization

Energy Technology Data Exchange (ETDEWEB)

Kelly, Ken; Smith, Kandler; Cosgrove, Jon; Prohaska, Robert; Pesaran, Ahmad; Paul, James; Wiseman, Marc

2015-12-01

Prepared for the U.S. Department of Energy, this milestone report focuses on the economics of leasing versus owning batteries for medium-duty hybrid electric vehicles as well as various battery standardization scenarios. The work described in this report was performed by members of the Energy Storage Team and the Vehicle Simulation Team in NREL's Transportation and Hydrogen Systems Center along with members of the Vehicles Analysis Team at Ricardo.

Base fluid in improving heat transfer for EV car battery

Science.gov (United States)

Bin-Abdun, Nazih A.; Razlan, Zuradzman M.; Shahriman, A. B.; Wan, Khairunizam; Hazry, D.; Ahmed, S. Faiz; Adnan, Nazrul H.; Heng, R.; Kamarudin, H.; Zunaidi, I.

2015-05-01

This study examined the effects of base fluid (as coolants) channeling inside the heat exchanger in the process of the increase in thermal conductivity between EV car battery and the heat exchanger. The analysis showed that secondary cooling system by means of water has advantages in improving the heat transfer process and reducing the electric power loss on the form of thermal energy from batteries. This leads to the increase in the efficiency of the EV car battery, hence also positively reflecting the performance of the EV car. The present work, analysis is performed to assess the design and use of heat exchanger in increasing the performance efficiency of the EV car battery. This provides a preface to the use this design for nano-fluids which increase and improve from heat transfer.

An Improved Parametrization Method for Li-ion Linear Static Equivalent Circuit Battery Models Based on Direct Current Resistance Measurement

DEFF Research Database (Denmark)

Barreras, Jorge Varela; Pinto, Claudio; de Castro, Ricardo

2015-01-01

response in the range of interest of many applications, including electro-mobility. Model validation and performance evaluation is achieved in simulations by comparison with other low and high order EECM battery models over dynamic driving profiles. Significant improvements in terms of cell terminal...

Physically-based impedance modeling of the negative electrode in All-Vanadium Redox Flow Batteries: insight into mass transport issues

International Nuclear Information System (INIS)

Zago, M.; Casalegno, A.

2017-01-01

Highlights: •Performance losses induced by migration though the porous electrode are negligible. •Convection at carbon fiber results in a linear branch at low frequency in Nyquist plot. •When the reaction is concentrated, diffusion losses though the electrode diminishes. •Diffusion process in the pores becomes more limiting at high current. •Charge transfer resistance decreases with increasing current. -- Abstract: Mass transport of the electrolyte over the porous electrode is one of the most critical issues hindering Vanadium Redox Flow Battery commercialization, leading to increased overpotential at high current and limiting system power density. In this work, a 1D physically based impedance model of Vanadium Redox Flow Battery negative electrode is developed, taking into account electrochemical reactions, convection at carbon fiber, diffusion in the pores and migration and diffusion through electrode thickness. The model is validated with respect to experimental data measured in a symmetric cell hardware, which allows to keep the State of Charge constant during the measurement. The physically based approach permits to elucidate the origin of different impedance features and quantify the corresponding losses. Charge transfer resistance decreases with increasing current and is generally lower compared to the ones related to mass transport phenomena. Migration losses through the porous electrode are negligible, while convection at carbon fiber is relevant and in Nyquist plot results in a linear branch at low frequency. In presence of significant convection losses the reaction tends to concentrate close to the channel: this leads to a reduction of diffusion losses through the electrode, while diffusion process in the pores becomes more limiting.

Inner ear test battery in guinea pig models - a review.

Science.gov (United States)

Young, Yi-Ho

2018-06-01

This study reviewed the development of the inner ear test battery comprising auditory brainstem response (ABR), and caloric, ocular vestibular-evoked myogenic potential (oVEMP), and cervical vestibular-evoked myogenic potential (cVEMP) tests in guinea pig models at our laboratory over the last 20 years. Detailed description of the methodology for testing the small animals is also included. Inner ear disorders, i.e. ototoxicity, noise exposure, or perilymph fistula were established in guinea pig models first. One to four weeks after operation, each animal underwent ABR, oVEMP, cVEMP, and caloric tests. Then, animals were sacrificed for morphological study in the temporal bones. Inner ear endorgans can be comprehensively evaluated in guinea pig models via an inner ear test battery, which provides thorough information on the cochlea, saccule, utricle, and semicircular canal function of guinea pigs. Coupled with morphological study in the temporal bones of the animals may help elucidate the mechanism of inner ear disorders in humans. The inner ear test battery in guinea pig models may encourage young researchers to perform basic study in animals and stimulate the progress of experimental otology which is in evolution.

Remaining Useful Life Prediction for Lithium-Ion Batteries Based on Gaussian Processes Mixture

Science.gov (United States)

Li, Lingling; Wang, Pengchong; Chao, Kuei-Hsiang; Zhou, Yatong; Xie, Yang

2016-01-01

The remaining useful life (RUL) prediction of Lithium-ion batteries is closely related to the capacity degeneration trajectories. Due to the self-charging and the capacity regeneration, the trajectories have the property of multimodality. Traditional prediction models such as the support vector machines (SVM) or the Gaussian Process regression (GPR) cannot accurately characterize this multimodality. This paper proposes a novel RUL prediction method based on the Gaussian Process Mixture (GPM). It can process multimodality by fitting different segments of trajectories with different GPR models separately, such that the tiny differences among these segments can be revealed. The method is demonstrated to be effective for prediction by the excellent predictive result of the experiments on the two commercial and chargeable Type 1850 Lithium-ion batteries, provided by NASA. The performance comparison among the models illustrates that the GPM is more accurate than the SVM and the GPR. In addition, GPM can yield the predictive confidence interval, which makes the prediction more reliable than that of traditional models. PMID:27632176

Metal hydrides based high energy density thermal battery

International Nuclear Information System (INIS)

Fang, Zhigang Zak; Zhou, Chengshang; Fan, Peng; Udell, Kent S.; Bowman, Robert C.; Vajo, John J.; Purewal, Justin J.; Kekelia, Bidzina

2015-01-01

Highlights: • The principle of the thermal battery using advanced metal hydrides was demonstrated. • The thermal battery used MgH 2 and TiMnV as a working pair. • High energy density can be achieved by the use of MgH 2 to store thermal energy. - Abstract: A concept of thermal battery based on advanced metal hydrides was studied for heating and cooling of cabins in electric vehicles. The system utilized a pair of thermodynamically matched metal hydrides as energy storage media. The pair of hydrides that was identified and developed was: (1) catalyzed MgH 2 as the high temperature hydride material, due to its high energy density and enhanced kinetics; and (2) TiV 0.62 Mn 1.5 alloy as the matching low temperature hydride. Further, a proof-of-concept prototype was built and tested, demonstrating the potential of the system as HVAC for transportation vehicles

A three-dimensional model for negative half cell of the vanadium redox flow battery

International Nuclear Information System (INIS)

Ma Xiangkun; Zhang Huamin; Xing Feng

2011-01-01

A stationary, isothermal, three-dimensional model for negative half cell of the vanadium redox flow battery is developed, which is based on the comprehensive conservation laws, such as charge, mass and momentum, together with a kinetic model for reaction involving vanadium species. The model is validated against the results calculated by the available two-dimensional model. With the given geometry of the negative half cell, the distributions of velocity, concentration, overpotential and transfer current density in the sections that are perpendicular and parallel to the applied current are studied. It is shown that the distribution of the electrolyte velocity in the electrode has significant impact on the distribution of concentration, overpotential and transfer current density. The lower velocity in the electrode will cause the higher overpotential, further result in the side reaction and corrosion of key materials locally. The development of the design of the vanadium redox flow battery is discussed, and the further research is proposed.

A high-energy-density redox flow battery based on zinc/polyhalide chemistry.

Science.gov (United States)

Zhang, Liqun; Lai, Qinzhi; Zhang, Jianlu; Zhang, Huamin

2012-05-01

Zn and the Art of Battery Development: A zinc/polyhalide redox flow battery employs Br(-) /ClBr(2-) and Zn/Zn(2+) redox couples in its positive and negative half-cells, respectively. The performance of the battery is evaluated by charge-discharge cycling tests and reveals a high energy efficiency of 81%, based on a Coulombic efficiency of 96% and voltage efficiency of 84%. The new battery technology can provide high performance and energy density at an acceptable cost. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Battery systems engineering

CERN Document Server

Rahn, Christopher D

2012-01-01

A complete all-in-one reference on the important interdisciplinary topic of Battery Systems Engineering Focusing on the interdisciplinary area of battery systems engineering, this book provides the background, models, solution techniques, and systems theory that are necessary for the development of advanced battery management systems. It covers the topic from the perspective of basic electrochemistry as well as systems engineering topics and provides a basis for battery modeling for system engineering of electric and hybrid electric vehicle platforms. This original

Graphene-Based Ultra-Light Batteries for Aircraft

Science.gov (United States)

Calle, Carlos I.; Kaner, Richard B.

2014-01-01

Develop a graphene-based ultracapacitor prototype that is flexible, thin, lightweight, durable, low cost, and safe and that will demonstrate the feasibility for use in aircraft center dot These graphene-based devices store charge on graphene sheets and take advantage of the large accessible surface area of graphene (2,600 m2/g) to increase the electrical energy that can be stored. center dot The proposed devices should have the electrical storage capacity of thin-film-ion batteries but with much shorter charge/discharge cycle times as well as longer lives center dot The proposed devices will be carbon-based and so will not have the same issues with flammability or toxicity as the standard lithium-based storage cells There are two main established methods for the storage and delivery of electrical energy: center dot Batteries - Store energy with electrochemical reactions - High energy densities - Slow charge/discharge cycles - Used in applications requiring large amounts of energy ? aircraft center dot Electrochemical capacitors - Store energy in electrochemical double layers - Fast charge/discharge cycles - Low energy densities - Used in electronics devices - Large capacitors are used in truck engine cranking

Remaining dischargeable time prediction for lithium-ion batteries using unscented Kalman filter

Science.gov (United States)

Dong, Guangzhong; Wei, Jingwen; Chen, Zonghai; Sun, Han; Yu, Xiaowei

2017-10-01

To overcome the range anxiety, one of the important strategies is to accurately predict the range or dischargeable time of the battery system. To accurately predict the remaining dischargeable time (RDT) of a battery, a RDT prediction framework based on accurate battery modeling and state estimation is presented in this paper. Firstly, a simplified linearized equivalent-circuit-model is developed to simulate the dynamic characteristics of a battery. Then, an online recursive least-square-algorithm method and unscented-Kalman-filter are employed to estimate the system matrices and SOC at every prediction point. Besides, a discrete wavelet transform technique is employed to capture the statistical information of past dynamics of input currents, which are utilized to predict the future battery currents. Finally, the RDT can be predicted based on the battery model, SOC estimation results and predicted future battery currents. The performance of the proposed methodology has been verified by a lithium-ion battery cell. Experimental results indicate that the proposed method can provide an accurate SOC and parameter estimation and the predicted RDT can solve the range anxiety issues.

Optimization of batteries for plug-in hybrid electric vehicles

Science.gov (United States)

English, Jeffrey Robb

This thesis presents a method to quickly determine the optimal battery for an electric vehicle given a set of vehicle characteristics and desired performance metrics. The model is based on four independent design variables: cell count, cell capacity, state-of-charge window, and battery chemistry. Performance is measured in seven categories: cost, all-electric range, maximum speed, acceleration, battery lifetime, lifetime greenhouse gas emissions, and charging time. The performance of each battery is weighted according to a user-defined objective function to determine its overall fitness. The model is informed by a series of battery tests performed on scaled-down battery samples. Seven battery chemistries were tested for capacity at different discharge rates, maximum output power at different charge levels, and performance in a real-world automotive duty cycle. The results of these tests enable a prediction of the performance of the battery in an automobile. Testing was performed at both room temperature and low temperature to investigate the effects of battery temperature on operation. The testing highlighted differences in behavior between lithium, nickel, and lead based batteries. Battery performance decreased with temperature across all samples with the largest effect on nickel-based chemistries. Output power also decreased with lead acid batteries being the least affected by temperature. Lithium-ion batteries were found to be highly efficient (>95%) under a vehicular duty cycle; nickel and lead batteries have greater losses. Low temperatures hindered battery performance and resulted in accelerated failure in several samples. Lead acid, lead tin, and lithium nickel alloy batteries were unable to complete the low temperature testing regime without losing significant capacity and power capability. This is a concern for their applicability in electric vehicles intended for cold climates which have to maintain battery temperature during long periods of inactivity