锂电池SOC与SOP的联合估计  

Joint Estimation of SOC and SOP of Lithium Battery

作　　者：张宵洋 张振福 于志豪[1] ZHANG Xiao-yang;ZHANG Zhen-fu;YU Zhi-hao(School of Marine Science and Engineering,Shandong University of Science and Technology,Qingdao 266590,China)

机构地区：[1]山东科技大学海洋科学与工程学院,山东青岛266590

出　　处：《控制工程》2022年第7期1255-1263,1309,共10页Control Engineering of China

基　　金：山东省自然科学基金资助项目(ZR2017MEE072)。

摘　　要：锂离子电池精确的荷电状态(SOC)和功率状态(SOP)对于电动汽车的稳定运行尤为重要,对此提出了一种锂电池SOC与多约束条件下SOP的联合估计方法。首先,建立了二阶RC等效电路模型,并运用迭代无迹卡尔曼滤波算法来估计荷电状态;然后,结合荷电状态的估计结果,在多约束条件下对SOP进行联合估计;最后,在动态应力工况和快速脉冲工况下对联合估计算法进行了MATLAB仿真测试验证。结果验证了所提联合估计算法对于SOC和SOP联合估计的有效性,并且具有较高的估计精度和较好的鲁棒性。The accurate state of charge(SOC)and state of power(SOP)of lithium-ion battery are very important for the stable operation of electric vehicle.Therefore,a joint estimation method of SOC and SOP under multiple constraints of lithium-ion battery is proposed in this paper.First,the second-order RC equivalent circuit model is established,and the iterative unscented Kalman filter(UKF)algorithm is used to estimate SOC.Then,combined with the estimation results of SOC,the SOP is jointly estimated under multiple constraints.Finally,under the condition of the dynamic stress test(DST)and fast pulse discharge,the joint estimation algorithm is verified by MATLAB simulation.The results show that the proposed joint estimation algorithm is effective for joint estimation of SOC and SOP,and has high estimation accuracy and robustness.

关 键 词：锂电池 荷电状态 功率状态 迭代无迹卡尔曼滤波 多约束条件 

分 类 号：TM912[电气工程—电力电子与电力传动]