荷电状态
分离器(采油)
阳极
电池(电)
阴极
材料科学
控制理论(社会学)
锂离子电池
联轴节(管道)
压力(语言学)
机械
冯·米塞斯屈服准则
电荷(物理)
计算机科学
锂电池
结构工程
泰勒级数
近似误差
还原(数学)
锂(药物)
桥接(联网)
国家(计算机科学)
作者
Yafang Zhang,Jinghui Li
标识
DOI:10.1002/ente.202502463
摘要
The expansion force is correlated with the battery's state of charge (SOC). To quantify the relationship between expansion force and SOC, this study establishes an electrochemical–mechanical coupling model to investigate the expansion force of lithium ions during charging and discharging processes, as well as the relationship between lithium concentration and stress. Simulation results show that at the end of charging, the expansion strain of anode is 0.04, while the cathode and separator exhibit compressive strains of 0.018 and 0.05, respectively, the von Mises stress of the separator is 0.06 MPa. Furthermore, the recurrent neural network, gated recurrent unit, and long short‐term memory (LSTM) algorithms are employed to estimate the SOC of battery, comparing the prediction accuracy with or without expansion force features. Incorporating expansion force features significantly improves SOC estimation accuracy, especially under complex US06 driving conditions, reducing the mean absolute error of the LSTM model to 0.43, a 62% reduction compared to models that do not include these features. The results of this study contribute to a better understanding of battery expansion behavior and enhance both SOC estimation accuracy and battery safety.
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