电源技术2024，Vol.48Issue(6)：1109-1115,7.DOI:10.3969/j.issn.1002-087X.2024.06.020
基于改进AFFRLS-AUKF的锂电池SOC估计
SOC estimation of lithium battery based on improved AFFRLS-AUKF
摘要
Abstract
The accurate estimation of the state of charge(SOC)of lithium batteries is one of the im-portant prerequisites for ensuring the safe and stable operation of battery management systems.In order to improve the accuracy of SOC estimation of lithium ion batteries,an SOC estimation method of lithium ion batteries combined improved adaptive forgetting factor least squares(AFFRLS)with adaptive unscented Kalman filter(AUKF)algorithm was proposed.The improved AFFRLS was used to identify the parameters of the established second-order RC equivalent circuit model,and the AUKF was used to estimate the SOC of lithium-ion batteries.The average absolute error of the joint estimation is 0.44%and the root mean square error is 0.61%through the verification of DST and UDDS conditions,which shows that the improved AFFRLS-AUKF method improves the accuracy and robustness of parameter identification and battery SOC estimation.关键词
锂离子电池/荷电状态/自适应遗忘因子/无迹卡尔曼滤波Key words
lithium-ion battery/state of charge/adaptive forgetting factor/unscented Kalman filtering分类
信息技术与安全科学引用本文复制引用
陈亮,卢玉斌,林正廉..基于改进AFFRLS-AUKF的锂电池SOC估计[J].电源技术,2024,48(6):1109-1115,7.基金项目
国家自然科学基金青年项目(NO.42202302) （NO.42202302）
