城轨车用超级电容器SOC的估算方法

针对城轨车辆储能用超级电容器的特点,建立等效电路模型。通过遗忘因子最小二乘算法识别模型参数,采用自适应无迹卡尔曼滤波(AUKF)算法估计超级电容器的荷电状态(SOC)。相比传统的卡尔曼滤波(KF)算法,AUKF算法循环迭代运算超级电容器的参数和SOC,可提高估算的准确度。利用混合脉冲功率特性(HPPC)实验,验证算法的可行性与准确性。KF算法的误差较大,最大误差为6%,平均误差为3%;AUKF算法的结果精度较高,平均误差约为1.5%。

SOC estimation method of supercapacitor for urban rail vehicles

An equivalent circuit model was established according to the performance characteristics of supercapacitors for urban rail vehicle energy storage.The model parameters were identified by the forgetting factor least squares algorithm,then adaptive unscented Kalman filter(AUKF) algorithm was used to estimate the state of charge(SOC) of the supercapacitor.Compared with the traditional Kalman filter(KF) algorithm,the AUKF algorithm iteratively calculated the parameters and SOC of the supercapacitor,improved the accuracy of estimation.Hybrid pulse power characteristic(HPPC) test was used to verify the feasibility and accuracy of the algorithm.The estimation error of KF algorithm was large.The maximum error of KF algorithm was 6%,the average error was 3%;the accuracy of AUKF algorithm was higher,its average error was about 1.5%.