摘要
为了精确估算电动汽车锂离子电池的荷电状态(SOC),采用多种等效电路模型,建立空间状态方程,通过带遗忘因子递推最小二乘法实时在线辨识电池模型参数,动态实时更新电池模型状态方程,利用Matlab对实验工况进行仿真,采用基于电池电路模型的联合FFRLS-EKF算法,在运算过程中加入电池健康状态(state of health,简称SOH)因子,得到的SOC估算值平均误差低于1.8%,最大误差低于3%。通过实验验证了FFRLS-EKF-SOC精确性,解决了误差累积问题。
In order to accurately estimate state of charge(SOC) of the electric car lithium-ion battery, the paper used a variety of equivalent circuit model and built space state equation, through real-time online with forgetting factor recursive least squares identification battery model parameters, dynamic real-time update battery model state equation, the experimental condition to make use of the Matlab simulation, based on the battery circuit model of joint FFRLS-EKF algorithm, and joined the battery state of health(SOH),The average error of the obtained SOC estimate is less than 1.8% and the maximum error is less than 3%.Finally, the accuracy of FFRLS-EKF-SOC is verified, and the error accumulation problem is solved.
作者
刘民
李少林
张景明
LIU Min;LI Shaolin;ZHANG Jingming(School of Mechatronic Engineering,Guilin University of Electronic Technology,Guilin 541004,China)
出处
《桂林电子科技大学学报》
2019年第2期130-134,共5页
Journal of Guilin University of Electronic Technology
基金
国家自然科学基金(61320106008)
广西图像图形智能处理重点实验室基金(GIIP201705)
桂林电子科技大学研究生教育创新计划(2017YJCX92,2018YJCX56)
关键词
荷电状态
锂离子电池
联合算法
模型参数
等效电路
健康状态因子
state of charge(SOC)
lithium-ion battery
combined algorithm
equivalent circuit
model parameters
state of health factor
