基于OCV分段拟合的电池SOC估计方法研究  

Research on State of Charge Estimation Method of Lithium Battery Based on Open-Circuit Voltage Piecewise Fitting

作　　者：杨朝红 马彬[1,2,3] 黄明浩 陈勇 YANG Zhao-hong;MA Bin;HUANG Ming-hao;CHEN Yong(School of Mechanical and Electrical Engineering,Beijing Information Science and Technology University,Beijing 100192,China;Collaborative Innovation Center of Electric Vehicles in Beijing,Beijing,100192,China;Beijing Laboratory for New Energy Vehicle,Beijing 100192,China)

机构地区：[1]北京信息科技大学机电工程学院,北京100192 [2]北京电动车辆协同创新中心,北京100192 [3]新能源汽车北京实验室,北京100192

出　　处：《计算机仿真》2021年第11期82-88,157,共8页Computer Simulation

基　　金：国家自然科学基金青年基金项目(51608040,);北京市自然科学基金青年项目(3174049);北京信息科技大学“勤信人才”培育计划项目(QXTCPC201701);北京信息科技大学科研重点培育项目(5211910942);北京信息科技大学科研水平提高重点培育项目(2020KYNH203);科技创新服务能力建设-北京实验室建设-新能源汽车北京实验室(PXM2019_014224_000005);科技创新服务能力建设-科研基地建设-北京实验室-新能源汽车北京实验室(PXM2018_014224_000011)。

摘　　要：电池OCV是影响观测矩阵协方差的关键,因此对锂电池SOC精确估计具有较大影响。根据锂电池SOC-OCV曲线的变化和观测噪声的时变特性,提出了基于OCV分段拟合的锂电池模糊自适应扩展卡尔曼滤波SOC估计方法。建立了锂电池二阶RC模型,通过实验辨识获得电池模型参数。采用分段拟合的方法获得电池精确SOC-OCV曲线,在降低拟合阶数、减少运算量的同时保证了拟合精度。基于模糊控制理论建立了观测噪声协方差模糊调节器,对观测噪声协方差矩阵进行实时调整从而提高算法的自适应能力。在UDDS工况下对算法进行了仿真分析,结果表明,上述算法可以有效提高SOC的估计精度,鲁棒性较好。研究结果为锂电池SOC动态、自适应、高鲁棒性估计方法提供理论依据。Battery OCV is the key to affect the covariance of the observation matrix, so it has a great impact on the accurate estimation of the lithium battery SOC. According to the change of SOC-OCV curve of lithium battery and the time-varying characteristics of observation noise, a fuzzy adaptive extended Kalman filter SOC estimation method based on OCV piecewise fitting is proposed. The second-order RC model of lithium battery is established, and the parameters of the battery model are obtained by experimental identification. The SOC-OCV curve of the battery is obtained by the piecewise fitting method, which can reduce the fitting order, reduce the calculation and ensure the fitting accuracy. Based on the fuzzy control theory, the observation noise covariance fuzzy regulator is established to adjust the observation noise covariance matrix in real-time to improve the adaptive ability of the algorithm. The simulation results show that the algorithm can effectively improve the estimation accuracy and robustness of SOC.The results provide a theoretical basis for SOC dynamic, adaptive and robust estimation of lithium batteries.

关 键 词：锂电池 荷电状态 扩展卡尔曼滤波 分段拟合 模糊调节器 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]