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影响因子：4.2

DOI码：10.1016/j.epsr.2026.113144

发表刊物：Electric Power Systems Research

关键字：Cylindrical LiFePO4 battery; Equivalent strain model; Covariance optimization matching adaptive extended kalman filter; SOC estimation

摘要：Lithium-ion batteries serve as one of the core components in electric vehicles, the state of charge (SOC) estimation accuracy significantly influences the overall performance of electric vehicles. This paper proposes a SOC estimation method for lithium-ion batteries based on an equivalent strain model and a covariance optimization matching adaptive extended Kalman filter (COMAEKF). Firstly, this paper introduces strain signals into the SOC estimation problem from the perspective of mechanical behaviors and establishes a nonlinear mapping relationship between open circuit strain and SOC via a 5th-order polynomial model. Secondly, a COMAEKF is developed to enhance the adaptability and convergence of the SOC estimation algorithm. Finally, experiment validations under various dynamic operating conditions and ambient temperatures show that the proposed methodology achieves high terminal strain estimation accuracy, with mean absolute error (MAE) below 2.60με and root mean square error (RMSE) below 3.75με Meanwhile, compared to the conventional ECM, it significantly improves the SOC estimation convergence speed and accuracy, with an initial SOC value set to 90%, the average convergence time is within 25 s, a reduction of over 94%, the average MAE remains below 0.50%, a reduction of over 82%, and the average RMSE stays below 0.65%, a reduction of over 85%.

备注：中科院3区

合写作者：Changpeng Tan

第一作者：Muyao Wu

论文类型：论文集

通讯作者：Li Wang

论文编号：113144

学科门类：工学

文献类型：J

卷号：258

ISSN号：0378-7796

是否译文：否

发表时间：2026-04-17

收录刊物：SCI、EI

发布期刊链接：https://www.sciencedirect.com/science/article/pii/S0378779626004372