适用于宽温度范围的锂离子电池SOC估计方法  

SOC estimation of lithium-ion batteries under multiple temperatures conditions based on MIARUKF algorithm

作　　者：胡雪峰[1] 常先雷 刘肖肖 徐威 张文彬 HU Xuefeng;CHANG Xianlei;LIU Xiaoxiao;XU Wei;ZHANG Wenbin(Anhui University of technology,Key Laboratory of Power Electronics and Motion Control in Anhui Province's Universities,Ma'anshan 243032,Anhui China)

机构地区：[1]安徽工业大学高校电力电子与运动控制重点实验室,安徽马鞍山243032

出　　处：《储能科学与技术》2024年第9期2983-2994,共12页Energy Storage Science and Technology

基　　金：安徽省教育厅自然科学基金(KJ2021A0372)。

摘　　要：精确的荷电状态(SOC)估计是确保动力电池安全稳定运行的关键所在。然而,在实际应用中,环境温度的变化以及噪声干扰等因素使得SOC的精确估计变得困难重重。为了解决这一问题,本文提出一种基于多新息自适应鲁棒无迹卡尔曼滤波(MIARUKF)算法的宽温度范围下锂离子电池SOC多时间尺度联合估计方法,该算法在无迹卡尔曼滤波(UKF)算法的基础上,融合多新息理论、自适应滤波与鲁棒算法。所提算法利用多新息向量对状态估计值进行修正,并对噪声协方差进行及时更新,从而提高SOC的估计精度,通过引入H∞滤波算法来提高该算法的鲁棒性。同时为了降低电池管理系统(BMS)的计算负担,使用UKF算法在宏观时间尺度上在线估计模型参数,采用MIARUKF算法在微观时间尺度上估计电池SOC。最后,在不同SOC初始值、不同温度条件下,对电池SOC的估计结果进行比较和分析,本文所提方法最大绝对误差和平均绝对误差分别为1.05%和0.42%,表明该算法具有较高的精度和较好的鲁棒性。Accurate state of charge(SOC)estimation is the key to ensure the safe and stable operation of power batteries.However,in practical applications,the environment factors such as temperature change and noise interference make the accurate estimation of SOC difficult.In order to solve this problem,this paper proposes a joint estimation method of multi-timescales of the SOC of lithium ion batteries in wide temperature range based on the multi-new interest adaptive robust untrace Kalman filter(MIARUKF)algorithm,which integrates multi-new interest theory,adaptive filtering and robust algorithm based on the UKF algorithm.The proposed algorithm uses the multi-interest vector to correct the state estimates and timely update the noise covariance,so as to improve the estimation accuracy of SOC and improve the robustness of the algorithm by introducing the H filtering algorithm.Meanwhile,in order to reduce the computational burden of BMS,the UKF algorithm was used to estimate the model parameters online on the macroscopic time scale,and the MIARUKF algorithm was used to estimate the battery SOC on the microscopic time scale.Finally,the estimation results of battery SOC were compared and analyzed under different initial SOC initial values and temperature conditions,and the maximum and average absolute errors of the proposed method were 1.05% and 0.42%,respectively,indicating the high accuracy and good robustness.

关 键 词：锂离子电池 荷电状态 多温度 多新息自适应鲁棒无迹卡尔曼滤波 

分 类 号：TM912[电气工程—电力电子与电力传动]