Abstract：Accurate state of charge (SOC) estimation is one of the important functions for battery management system. Currently, the model-based approach is the most widely used solution for lithium-ion battery SOC estimation. Compared with the equivalent circuit model (ECM), the electrochemical model (EM) has gradually become the research focus of the next generation advanced battery management systems due to its ability to estimate the SOC coupled with electrochemical mechanism. However, the existing review studies of the model-based battery SOC estimation methods are mostly focused on ECMs, and the EMs are rarely discussed systematically. For this reason, the EM-based SOC estimation algorithms are reviewed in this paper. First, the modeling and parameter identification methods of EMs are summarized, and the existing approaches to EM-based SOC estimation are discussed. Then, existing challenges and the future prospects of the EM-based SOC estimation are presented. The insights presented in this paper are expected to catalyze the development and application of the EM-based advanced battery management system algorithms.
武龙星, 庞辉, 晋佳敏, 耿院飞, 刘凯. 基于电化学模型的锂离子电池荷电状态估计方法综述[J]. 电工技术学报, 2022, 37(7): 1703-1725.
Wu Longxing, Pang Hui, Jin Jiamin, Geng Yuanfei, Liu Kai. A Review of SOC Estimation Methods for Lithium-Ion Batteries Based on Electrochemical Model. Transactions of China Electrotechnical Society, 2022, 37(7): 1703-1725.
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