State of Charge Estimation Comparative Analysis for Traction Li-ion 
Batteries in Electric Vehicle

doi:10.16638/j.cnki.1671-7988.2023.015.009

Abstract

Abstract: Because the lithium-ion battery of electric vehicles is a time-varying and nonlinear complex electrochemical system during use, it is difficult to accurately evaluate state of charge (SOC). In this paper, SOC estimation methods for lithium-ion batteries of electric vehicles are reviewed in detail, according to the different characteristics of various algorithms, they are divided into traditional methods, learning algorithm-based methods and model-based methods, the characteristics and application conditions of various estimation methods are expounded, and the advantages and disadvantages of each method are analyzed and discussed, and the future online SOC estimation methods for lithium-ion batteries of electric vehicles are prospected. The results show that the SOC estimation method based on learning algorithm will be the future development direction.

Key words: Electric vehicles; Lithium-ion battery; State of charge; Kalman filter

摘要： 由于电动汽车动力锂离子电池在使用过程中是时变、非线性的复杂电化学系统，精确评估电池荷电状态（SOC）难度很大。文章对电动汽车锂离子电池的 SOC 估算方法进行了详细综述，根据各类算法的不同特征将其分为传统方法、基于学习算法的方法和基于模型的方法，阐明了各种估算方法的特征及应用条件，对各种方法的优缺点进行了分析探讨，对将来在线估算电动汽车锂离子电池 SOC 的方法进行了展望。结果表明，基于学习算法的 SOC 估算方法将是未来的发展方向。

关键词: 电动汽车；锂离子电池；荷电状态；卡尔曼滤波

WU Guangshun. State of Charge Estimation Comparative Analysis for Traction Li-ion Batteries in Electric Vehicle[J]. Automobile Applied Technology, 2023, 48(15): 47-53.

吴广顺. 电动汽车动力锂离子电池 SOC 估算方法比较分析[J]. 汽车实用技术, 2023, 48(15): 47-53.

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