基于SRCKF算法的锂离子电池荷电状态估计  

State of charge estimation of Li-ion battery based on SRCKF algorithm

作　　者：肜瑶[1] 张洋洋[1] 吕运朋[2] RONG Yao;ZHANG Yangyang;LYU Yunpeng(Engineering Department,Huanghe S&T University,Zhengzhou 450063,Henan,China;School of Physics,Zhengzhou University,Zhengzhou 450001,Henan,China)

机构地区：[1]黄河科技学院工学部,河南郑州450063 [2]郑州大学物理学院,河南郑州450001

出　　处：《电池》2025年第2期273-278,共6页Battery Bimonthly

基　　金：河南省级科技攻关项目(23210221003)。

摘　　要：为提高荷电状态(SOC)估计的精度,以磷酸铁锂锂离子电池为研究对象,在双极化等效电路模型的基础上,分析容积卡尔曼滤波器(CKF)的SOC估计过程。针对CKF算法发散的问题,采用平方根容积卡尔曼滤波(SRCKF)算法进行电池SOC估计。SRCKF算法通过引入正交三角(QR)分解,误差协方差矩阵在计算过程中以平方根的形式传播,从而确保矩阵的正定和对称。与CKF算法对比发现,SRCKF算法的估计误差为2.0534×10-4 V,说明可以提高SOC估计的精度。In order to improve the accuracy of state of charge(SOC)estimation,the lithium iron phosphate Li-ion battery is taken as the research object,the SOC estimation process of the cubature Kalman filter(CKF)is analyzed on the basis of the dual polarized equivalent circuit model.The square root cubature Kalman filter(SRCKF)algorithm for battery SOC estimation is investigated,with respect to the dispersion problem of the CKF algorithm.The algorithm ensures the positivity and symmetry of the matrix by introducing the orthogonal-triangular(QR)decomposition so that the error covariance matrix is propagated by the square root during the computation process.The comparison with the conventional CKF algorithm shows that the estimation error of the SRCKF algorithm is 2.0534×10-4 V,indicates that it can improve the estimation accuracy of SOC.

关 键 词：磷酸铁锂锂离子电池 双极化模型 平方根容积卡尔曼滤波(SRCKF)算法 荷电状态(SOC)估计 

分 类 号：TM912.9[电气工程—电力电子与电力传动]