A review of lithium ion batteries electrochemical models for electric vehicles

The electrochemical model can reflect the electrochemical reactions inside the lithium ion battery, and the model parameters have practical physical significance. Therefore, it is commonly used in the simulation research of the life prediction and the cell decay mechanism analysis of the lithium ion battery. This paper mainly introduces three commonly used electrochemistry models: P2D model, SP model and extended SP model. The origin and research progress of three kinds of electrochemical models are described. The characteristics of the three models are analyzed and compared. P2D model can describe the battery reactions comprehensively, but the iterative solution is complicated. The SP model simplifies some electrochemical reactions and improves the computational speed of the model, but the accuracy is decreased. In order to solve the shortcoming of SP model, the electrochemical reaction omitted from SP model is introduced again, and the approximate solution is solved by mathematical method, so as to realize the balance between precision and computational complexity of the model. Based on the above analysis and the application scenarios of lithium ion battery, the further development of the lithium ion battery electrochemical model is prospected.

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Modeling and Simulation Research on Lithium-Ion Battery in Electric Vehicles Based on Genetic Algorithm

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.494-495.246 ◽

2014 ◽

Vol 494-495 ◽

pp. 246-249

Author(s):

Cheng Lin ◽

Xiao Hua Zhang

Keyword(s):

Genetic Algorithm ◽

Lithium Ion Battery ◽

Stress Test ◽

Lithium Ion ◽

Model Parameters ◽

Test Accuracy ◽

Battery Management System ◽

Battery Management ◽

Simulation Research ◽

Battery Model

Based on the genetic algorithm (GA), a novel type of parameters identification method on battery model was proposed. The battery model parameters were optimized by genetic optimization algorithm and the other parameters were identified through the hybrid pulse power characterization (HPPC) test. Accuracy and efficiency of the battery model were validated with the dynamic stress test (DST). Simulation and experiment results shows that the proposed model of the lithium-ion battery with identified parameters was accurate enough to meet the requirements of the state of charge (SoC) estimation and battery management system.

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A Nonlinear Observer SOC Estimation Method Based on Electrochemical Model for Lithium-Ion Battery

IEEE Transactions on Industry Applications ◽

10.1109/tia.2020.3040140 ◽

2021 ◽

Vol 57 (1) ◽

pp. 1094-1104

Author(s):

Yuntian Liu ◽

Rui Ma ◽

Shengzhao Pang ◽

Liangcai Xu ◽

Dongdong Zhao ◽

...

Keyword(s):

Lithium Ion Battery ◽

Estimation Method ◽

Lithium Ion ◽

Nonlinear Observer ◽

Soc Estimation ◽

Electrochemical Model

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Electrochemical Model-Based Investigation of Thick LiFePO4 Electrode Design Parameters

Modelling ◽

10.3390/modelling2020014 ◽

2021 ◽

Vol 2 (2) ◽

pp. 259-287

Author(s):

Robert Franke-Lang ◽

Julia Kowal

Keyword(s):

Lithium Ion Batteries ◽

Porous Electrode ◽

Lithium Ion ◽

Size Composition ◽

Design Parameters ◽

Model Parameters ◽

Electrode Structure ◽

Transport Channel ◽

Scale Particle ◽

Electrochemical Model

The electrification of the powertrain requires enhanced performance of lithium-ion batteries, mainly in terms of energy and power density. They can be improved by optimising the positive electrode, i.e., by changing their size, composition or morphology. Thick electrodes increase the gravimetric energy density but generally have an inefficient performance. This work presents a 2D modelling approach for better understanding the design parameters of a thick LiFePO4 electrode based on the P2D model and discusses it with common literature values. With a superior macrostructure providing a vertical transport channel for lithium ions, a simple approach could be developed to find the best electrode structure in terms of macro- and microstructure for currents up to 4C. The thicker the electrode, the more important are the direct and valid transport paths within the entire porous electrode structure. On a smaller scale, particle size, binder content, porosity and tortuosity were identified as very impactful parameters, and they can all be attributed to the microstructure. Both in modelling and electrode optimisation of lithium-ion batteries, knowledge of the real microstructure is essential as the cross-validation of a cellular and lamellar freeze-casted electrode has shown. A procedure was presented that uses the parametric study when few model parameters are known.

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Evaluation and observability analysis of an improved reduced-order electrochemical model for lithium-ion battery

Electrochimica Acta ◽

10.1016/j.electacta.2020.137604 ◽

2021 ◽

Vol 368 ◽

pp. 137604

Author(s):

Longxing Wu ◽

Kai Liu ◽

Hui Pang

Keyword(s):

Lithium Ion Battery ◽

Lithium Ion ◽

Reduced Order ◽

Observability Analysis ◽

Electrochemical Model

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Three-Dimensional Thermal Model of a Lithium Ion Battery for Hybrid Mobile Working Machines: Determination of the Model Parameters in a Pouch Cell

IEEE Transactions on Energy Conversion ◽

10.1109/tec.2013.2255291 ◽

2013 ◽

Vol 28 (2) ◽

pp. 335-343 ◽

Cited By ~ 38

Author(s):

Kirill Murashko ◽

Juha Pyrhonen ◽

Lasse Laurila

Keyword(s):

Lithium Ion Battery ◽

Thermal Model ◽

Three Dimensional ◽

Lithium Ion ◽

Model Parameters ◽

Mobile Working

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A Physics-Based Electrochemical Model for Lithium-Ion Battery State-of-Charge Estimation Solved by an Optimised Projection-Based Method and Moving-Window Filtering

Energies ◽

10.3390/en11082120 ◽

2018 ◽

Vol 11 (8) ◽

pp. 2120 ◽

Cited By ~ 16

Author(s):

Wei He ◽

Michael Pecht ◽

David Flynn ◽

Fateme Dinmohammadi

Keyword(s):

Lithium Ion Battery ◽

Solid Phase ◽

Chemical Properties ◽

Lithium Ion ◽

State Of Charge ◽

Critical Parameters ◽

Estimation Accuracy ◽

Moving Window ◽

Battery Management ◽

Electrochemical Model

State-of-charge (SOC) is one of the most critical parameters in battery management systems (BMSs). SOC is defined as the percentage of the remaining charge inside a battery to the full charge, and thus ranges from 0% to 100%. This percentage value provides important information to manufacturers about the performance of the battery and can help end-users identify when the battery must be recharged. Inaccurate estimation of the battery SOC may cause over-charge or over-discharge events with significant implications for system safety and reliability. Therefore, it is crucial to develop methods for improving the estimation accuracy of battery SOC. This paper presents an electrochemical model for lithium-ion battery SOC estimation involving the battery’s internal physical and chemical properties such as lithium concentrations. To solve the computationally complex solid-phase diffusion partial differential equations (PDEs) in the model, an efficient method based on projection with optimized basis functions is presented. Then, a novel moving-window filtering (MWF) algorithm is developed to improve the convergence rate of the state filters. The results show that the developed electrochemical model generates 20 times fewer equations compared with finite difference-based methods without losing accuracy. In addition, the proposed projection-based solution method is three times more efficient than the conventional state filtering methods such as Kalman filter.

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