荷电状态
电池(电)
扩展卡尔曼滤波器
卡尔曼滤波器
等效电路
锂(药物)
多项式的
锂离子电池
控制理论(社会学)
查阅表格
算法
计算机科学
电压
数学
统计
工程类
热力学
功率(物理)
电气工程
物理
人工智能
程序设计语言
医学
数学分析
控制(管理)
内分泌学
作者
Jiabin Wang,Jianhua Du,B. T. G. Tan,Xin Cao,Qu Chang,Yun Ou,Xingfeng He,Ling Xiong,Ran Tu
出处
期刊:Journal of The Electrochemical Society
[The Electrochemical Society]
日期:2023-12-01
卷期号:170 (12): 120507-120507
标识
DOI:10.1149/1945-7111/ad11af
摘要
Accurate estimation of the state-of-charge (SOC) is essential to prevent overcharging and over-discharging of lithium-ion batteries. However, traditional SOC estimation methods exhibit significant errors under large temperature variations due to the strong temperature dependence of battery characteristics. To enhance the accuracy of SOC estimation, this study proposes a second-order RC equivalent circuit model with temperature correction. By considering the influence of temperature on model parameters, the model’s accuracy is improved by adjusting the estimated parameters. A polynomial coefficient data table for model parameters is established to expedite the computation time of the SOC estimation process. Finally, the temperature-corrected model is combined with an Adaptive Extended Kalman Filter (AEKF) algorithm for SOC estimation. The results of the Dynamic Stress Test (DST) condition experiments show that the temperature correction model can improve the accuracy of SOC estimation under different temperature conditions. It has a more lower SOC estimation error than the model without temperature correction.
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