基于扩展卡尔曼滤波的钠离子电池SOC估计  

SOC estimation of sodium-ion battery based on extended Kalman filter

作　　者：张福建 赵席 郑新月 邓富金 ZHANG Fujian;ZHAO Xi;ZHENG Xinyue;DENG Fujin(School of Intelligent Manufacturing and Control,Shanghai Second Polytechnic University,Shanghai 201209,China;School of Electrical Engineering,Southeast University,Nanjing 210000,Jiangsu,China)

机构地区：[1]上海第二工业大学智能制造与控制工程学院,上海201209 [2]东南大学电气工程学院,江苏南京210000

出　　处：《电池》2025年第1期99-103,共5页Battery Bimonthly

基　　金：国家自然科学基金(52277173)。

摘　　要：精确估计荷电状态(SOC)对于钠离子电池的合理使用至关重要。以18650型钠离子电池作为研究对象,在实验室钠离子电池阶段放电实验数据基础上,建立二阶RC等效电路模型,利用PyCharm软件进行SOC曲线仿真,对比扩展卡尔曼滤波(EKF)算法估计的SOC曲线与实际曲线,验证算法的有效性和鲁棒性。增加补偿电压后,EKF算法能较好地估计电池的SOC,平均误差为1.79%,整体模型精度优于标准卡尔曼滤波算法,且最大误差减少了1.6个百分点,同时针对不同SOC初值具有良好的鲁棒性。Accurate estimation of state of charge(SOC)is important for the rational use of the sodium-ion battery.The 18650 type sodium-ion battery is taken as the research object,on the basis of the data of sodium-ion battery stage discharge experiment of the laboratory,the second-order RC equivalent circuit model is established.The SOC curve is simulated by using the PyCharm software,the SOC curve estimated by the extended Kalman filtering(EKF)algorithm is compared with the actual curve to verify the effectiveness and robustness of the algorithm.After adding the compensation voltage,the EKF algorithm can better estimate the SOC of the battery with an average error of 1.79%,the overall model accuracy is better than the traditional Kalman filter algorithm,the maximum error is reduced by 1.6 percentage points.It also has good robustness for different SOC initial values.

关 键 词：钠离子电池 扩展卡尔曼滤波(EKF)算法 二阶RC等效电路 荷电状态(SOC) 补偿电压 

分 类 号：TM912.9[电气工程—电力电子与电力传动] TD98[矿业工程—选矿]