摘要
本文针对车用锂电池的高精度SOC估计方法进行研究,首先选取二阶Thevenin等效电路作为本文锂电池的等效电路模型,针对车用锂电池复杂工况难以在线辨识的等效模型参数的问题,提出使用移动指数窗的LS算法在线辨识锂电池的等效电路模型参数,最后通过粒子滤波算法估计SOC。仿真和实验验证了在车用锂电池中使用移动指数窗的LS算法辨识等效电路模型参数具有较高的精度,且SOC估计精度得到提高。
This paper studies the high-precision SOC estimation method of lithium battery for vehicles.First, the second-order Thevenin equivalent circuit is selected as the equivalent circuit model of lithium battery in this paper.In this paper, the LS algorithm of moving exponential window is proposed to identify the equivalent circuit model parameters of lithium battery online, and finally the SOC is estimated by particle filter algorithm.Simulation and experiments verify that the LS algorithm using the moving exponential window in the vehicle lithium battery can identify the parameters of the equivalent circuit model with high accuracy, and the SOC estimation accuracy is improved.
作者
谢臻杰
林琼斌
詹银
陈斐泓
XIE Zhen-jie;LIN Qiong-bin;ZHAN Yin;CHEN Fei-hong(School of Electrical Engineering and Automation Fuzhou University Fuzhou 350108,China;Power Construction Corporation of China Fujian Electric Power Survey Design Institute Co.Ltd.,Fuzhou 350003,China)
出处
《电气开关》
2022年第6期36-40,共5页
Electric Switchgear
基金
福建省自然科学基金(2021J01637)。
关键词
新能源汽车
参数辨识
最小二乘法
粒子滤波
new energy vehicle
parameter identification
recursive least squares method
particle filter
