自适应无迹卡尔曼滤波动力电池的SOC估计OA北大核心CSCDCSTPCD
SOC estimation of power battery based on AUKF
无迹卡尔曼滤波法(Unscented-Kalman Filter,UKF)在估计动力电池的剩余容量(State of Charge,SOC)时,由于系统噪声的不确定,可能导致算法不收敛,而且算法的估计性能受模型精度的影响,为此采用自适应无迹卡尔曼滤波法(Adaptive-UKF,AUKF)动态估计电动汽车动力电池的SOC.建立了适用于SOC估计的电池模型,辨识相应的电池模型的参数并进行验证,将AUKF应用到该模型,在未知干扰噪声环境下,在线估计电…查看全部>>
The UKF method can be used to estimate the SOC of power battery,however,the uncertainty of the system noise may cause that the algorithm does not converge,and the estimation performance of the algorithm is affected by the accuracy of the model.An AUKF is used to estimate the dynamic SOC of an electric vehicle.At first,an equivalent circuit model appropriate for SOC estimation is built and the corresponding parameters of the battery model are identified…查看全部>>
谢永东;何志刚;陈栋;周洪剑
江苏职业联合技术学院苏州建设交通分院,江苏苏州215000江苏大学汽车与交通工程学院,江苏镇江212013江苏大学汽车与交通工程学院,江苏镇江212013江苏大学汽车与交通工程学院,江苏镇江212013
信息技术与安全科学
电动汽车动力电池SOC估计自适应无迹卡尔曼滤波
electric vehiclepower batterySOC estimationadaptive unscented Kalman filter
《北京交通大学学报》 2018 (2)
129-137,9
国家科技支撑计划项目(2015BAG07B00)National Key Technology Research and Development Program(2015BAG07B00)
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