基于FFRLS和GSAPF的锂电池剩余电量估计  

SOC Estimation of Lithium Battery Based on FFRLS and GSAPF

作　　者：王郑 卢昊 程静 蒋兆国 刘建晟 Wang Zheng;Lu Hao;Cheng Jing

机构地区：[1]江苏理工学院汽车与交通工程学院,江苏常州213001

出　　处：《装备机械》2024年第3期78-81,72,共5页The Magazine on Equipment Machinery

基　　金：江苏省大学生创新创业训练计划项目(编号:202311463071Y)。

摘　　要：新能源汽车的稳定运行依赖于锂电池的剩余电量估计。对此,提出一种基于遗忘因子递推最小二乘法(FFRLS)和黄金正弦粒子滤波算法(GSAPF)的锂电池剩余电量估计方法。这一方法在使用递推最小二乘法对锂电池进行参数辨识的基础上,引入遗忘因子,通过遗忘因子重新分配旧数据和新数据的权重,从而减少递推最小二乘法的数据饱和现象,并且联合黄金正弦粒子滤波算法对锂电池进行剩余电量估计。试验结果表明,这一方法具有较高的精度。The stable operation of new energy vehicle depends on the SOC estimation of lithium battery.In this regard,an SOC estimation method of lithium battery based on FFRLS and GSAPF was proposed.On the basis of using RLS to identify the parameter of lithium battery,the forgetting factor was introduced,and the weights of old data and new data were redistributed through the forgetting factor,so as to reduce the data saturation phenomenon of RLS,and the SOC of lithium battery was estimated by combining GSAPF.Experimental result shows that this method has high precision.

关 键 词：锂电池 剩余电量 估计 遗忘因子递推最小二乘法 黄金正弦粒子滤波算法 

分 类 号：TM912[电气工程—电力电子与电力传动]