摘要
针对一阶离散滑模观测器法出现明显抖振现象,提出了基于二阶离散滑模观测器的SOC估计法。以二阶RC等效电路模型为基础,采用变遗忘因子最小二乘法在线辨识模型参数,提出一种锂电池模型参数和SOC在线估计方法,并与一阶离散滑模观测器法进行了对比试验研究。试验结果表明所设计滑模观测器具有较高SOC估计精度,未出现明显抖振现象,可进一步保证SOC在线估计的可靠性。
To solve the issue on obvious chattering phenomenon in SOC online estimation process based on the first-order discrete-time sliding mode observer（ 1-DSMO） algorithm,the second-order DSMO（ 2-DSMO） was proposed and its stability is shown. The variable forgetting factor recursive least squares（ VFFRLS） method was used to identify model parameters online based on the second-order RC equivalent circuit model and further to form the SOC estimation method using VFFRLS and 2-DSMO algorithms. The experimental results show that the proposed method using 2-DSMO algorithm has higher estimation accuracy than 1-DSMO algorithm,and is without obvious chattering phenomenon. The reliability of the proposed method has been verified.
出处
《电器与能效管理技术》
2018年第3期43-46,52,共5页
Electrical & Energy Management Technology
基金
河南省科技攻关项目(172102210069)
关键词
锂电池
荷电状态
二阶离散滑模观测器
变遗忘因子最小二乘法
lithium-ion battery
state of charge （ SOC ）
second-order discrete-time sliding mode observer （ 2-DSMO ）
variable forgetting factor recursive least squares （ VFFRLS ）
