点击次数：

影响因子：9.0

DOI码：10.1016/j.energy.2023.128437

发表刊物：Energy

关键字：LiFePO4 Power Battery, Forgetting Factor Recursive Total Least Squares, Temperature Correction, Capacity Convergence Coefficient, Arrhenius Equation

摘要：The decline of the lithium-ion power battery's State of Health (SOH) with usage significantly impacts other state estimation results, such as State of Charge (SOC). Hence, accurate estimation of the lithium-ion power battery's SOH holds vital importance in the battery management system. This paper proposes a SOH estimation method for the lithium-ion power battery, utilizing the Forgetting Factor Recursive Total Least Squares (FFRTLS) and incorporating the temperature correction. The FFRTLS effectively addresses the SOC estimation errors and the terminal current measurement noise simultaneously. The temperature correction method, based on the Arrhenius equation, corrects the influence of the ambient temperature during the SOH estimation process, ensuring that the ambient temperature does not affect the accuracy of the SOH estimation results. Additionally, the capacity convergence coefficient enhances the reliability of the SOH estimation results by preventing abrupt changes of the maximum available capacity. Experimental results on a LiFePO4 power battery under diverse working conditions and varying ambient temperatures, validate the effectiveness of the proposed method. The evaluation indexes, including Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Maximum Absolute Error (Max-AE), demonstrate the high accuracy of the SOH estimation results, with all indexes below 0.21%, 0.25% and 0.35% respectively.

备注：中科院1区Top

合写作者：Li Wang

第一作者：Muyao Wu

论文类型：期刊论文

通讯作者：Ji Wu

论文编号：128437

学科门类：工学

文献类型：J

卷号：282

ISSN号：0360-5442

是否译文：否

发表时间：2023-07-13

收录刊物：SCI、EI

发布期刊链接：https://www.sciencedirect.com/science/article/pii/S0360544223018315