MAFFRLS算法辨识锂离子电池模型参数  

Parameter identification of Li-ion battery model by MAFFRLS algorithm

作　　者：王迪 曹以龙 杜君莉 WANG Di;CAO Yilong;DU Junli(School of Electric Power Engineering,Zhengzhou Electric Power College,Zhengzhou,Henan 450000,China;College of Electronics and Information Engineering,Shanghai University of Electric Power,Shanghai 200000,China;State Grid Henan Electric Power Company Electric Power Science Research Institute,Zhengzhou,Henan 450000,China)

机构地区：[1]郑州电力高等专科学校电力工程学院,河南郑州450000 [2]上海电力大学电子与信息工程学院,上海200000 [3]国网河南省电力公司电力科学研究院,河南郑州450000

出　　处：《电池》2024年第2期189-193,共5页Battery Bimonthly

基　　金：中国博士后科学基金第3批特别资助(2021TQ0097);河南省科技厅重点研发与推广专项项目(232102240063);河南省高等学校重点科研项目(23B470006)。

摘　　要：建模方法和模型参数辨识方法会影响锂离子电池状态的准确估计,特别是在动态工况下,因此在线辨识电池模型参数的方法很重要。提出一种改进的自适应遗忘因子递推最小二乘(MAFFRLS)法,优点是在不同误差范围内可以自适应地更新遗忘因子最优值。选用二阶RC等效电路模型,在动态工况下对该算法进行验证。将所提出的算法与递推最小二乘(RLS)法和遗忘因子递推最小二乘(FFRLS)法进行对比。在动态应力测试(DST)工况下,使用RLS、FFRLS和MAFFRLS算法估计电压,平均绝对误差分别为0.0102 V、0.0099 V和0.0046 V,均方根误差分别为0.0155 V、0.0150 V和0.0068 V。MAFFRLS算法的平均绝对误差和均方根误差更小,准确性更高。The modeling method and the method of model parameter identification will affect the accurate estimation of the Li-ion battery state,especially under dynamic conditions.Therefore,the method of online identification of battery model parameters is very important.A modified adaptive forgetting factor recursive least squares(MAFFRLS)method is proposed,its superiority is that the optimal value of the forgetting factor can be adaptively updated within different error ranges.A second-order RC equivalent circuit model is chosen to validate the algorithm under dynamic operating conditions.The proposed algorithm is compared with the recursive least squares(RLS)method and the forgetting factor recursive least squares(FFRLS)method.Under the dynamic stress test(DST)condition,the voltage is estimated using the RLS,FFRLS and MAFFRLS algorithms with the average absolute error of 0.0102 V,0.0099 V and 0.0046 V,respectively.The root mean square error is 0.0155 V,0.0150 V and 0.0068 V.The MAFFRLS algorithm has a smaller mean absolute error and root mean square error,the accuracy is higher.

关 键 词：电池模型 等效电路模型 自适应 遗忘因子递推最小二乘(FFRLS)法 

分 类 号：TM912.9[电气工程—电力电子与电力传动]