A Physics-Based Equivalent Circuit Model and State of Charge Estimation for Lithium-Ion Batteries

Yigang Li (), Hongzhong Qi, Xinglei Shi, Qifei Jian, Fengchong Lan and Jiqing Chen
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Yigang Li: GAC Automotive Research & Development Center, Guangzhou 511434, China
Hongzhong Qi: GAC Automotive Research & Development Center, Guangzhou 511434, China
Xinglei Shi: GAC Automotive Research & Development Center, Guangzhou 511434, China
Qifei Jian: School of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou 510641, China
Fengchong Lan: School of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou 510641, China
Jiqing Chen: School of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou 510641, China

Energies, 2024, vol. 17, issue 15, 1-31

Abstract: This paper proposes a novel physics-based equivalent circuit model of the lithium-ion battery for electric vehicle applications that has comprehensive electrochemical significance and an acceptable level of complexity. Initially, the physics-based extended single particle (ESP) model is improved by adding a correction term to mitigate its voltage bias. Then, the equivalent circuit model based on the improved extended single particle (ECMIESP) model is derived. In this model, the surface state of charge (SOC) of solid particles is approximated using a capacity and multi first-order resistance-capacity equivalent circuits with only two lumped parameters. The overpotential of electrolyte diffusion is approximated using a first-order resistance-capacitance equivalent circuit. The electrochemical reaction overpotential is characterized by a nonlinear resistance. The voltage accuracies of ECMIESP and conventional 2RC equivalent circuit model (ECM2RC) are compared across the entire SOC range under various load profiles. The results demonstrate that the ECMIESP model outperforms ECM2RC model, particularly at low SOC or when the electrochemical reaction overpotential exceeds 50 mV. For instance, the ECMIESP model shows an 820.4 mV reduction in voltage error compared to the ECM2RC model at the endpoint during a 2C constant current discharge test. Lastly, the ECMIESP model was used for SOC estimation with extended Kalman filter, resulting in significantly improved accuracy compared to the conventional ECM2RC model. Therefore, the ECMIESP model has great potential for real-time applications in enhancing voltage and SOC estimation precision.

Keywords: lithium-ion battery; electric vehicle; extended single particle model; physics based; equivalent circuit model; state of charge (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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