基于EKF的钛酸锂电池SOC估计  

SOC estimation of lithium titanate battery based on EKF

作　　者：廖友萍 李睿[2] 吕航 张付军[1] 赵长禄[1] LIAO Youping;LI Rui;LV Hang;ZHANG Fujun;ZHAO Changlu(School of Mechanical Engineering,Beijing Institute of Technology,Beijing 100081,China;China North Vehicle Research Institute,Beijing 100072,China)

机构地区：[1]北京理工大学机械与车辆学院,北京100081 [2]中国北方车辆研究所,北京100072

出　　处：《电源技术》2023年第5期639-643,共5页Chinese Journal of Power Sources

基　　金：国家部委基金项目(2019-JCJQ-ZD-362-02-01)。

摘　　要：精确的荷电状态(SOC)估计可以保障电池系统安全可靠地工作。钛酸锂电池优良的大倍率充放电特性使其近年来在需要大功率充放电的特种车辆上得到应用。针对使用扩展卡尔曼滤波算法估计SOC在不同模型上产生不同误差的问题,以钛酸锂电池为实验对象,针对最常用的一阶RC和二阶RC模型,利用实验数据进行了参数辨识,开展了三种不同工况下的SOC仿真研究,结果表明:两种模型的扩展卡尔曼滤波算法精度都较高,平均相对误差都在2%以内。在恒定工况下,一阶RC模型的扩展卡尔曼滤波算法有更高的精度,而在变工况下,一阶RC模型的扩展卡尔曼滤波算法比二阶RC模型精度略低,表明二阶RC模型具有更好的动态性能。Accurate SOC estimation ensures safe and reliable operation of battery systems.The excellent high-rate charge-discharge characteristics of lithium titanate batteries make them used in special vehicles that require highpower charge and discharge in recent years.In view of the problem that using the extended Kalman filter algorithm to estimate SOC produces different errors on different models,in this paper,lithium titanate battery is used as the test object,for the most commonly used the first-order RC and the second-order RC models,parameter identification was carried out using experimental data,and SOC simulation studies under three different working conditions were carried out.The results show that the accuracy of the extended Kalman filter algorithm of the two models is high,and the average relative error is within 2%.Under constant operating conditions,the extended Kalman filtering algorithm of the first-order RC model has higher accuracy,while under variable operating conditions,the extended Kalman filtering algorithm of the first-order RC model is slightly less accurate than the second-order RC model,indicating that the second-order RC model has better dynamic performance.

关 键 词：钛酸锂电池 SOC估计 扩展卡尔曼滤波 在线参数辨识 

分 类 号：TM912[电气工程—电力电子与电力传动]