北京交通大学学报2018，Vol.42Issue(2)：129-137,9.DOI:10.11860/j.issn.1673-0291.2018.02.018
自适应无迹卡尔曼滤波动力电池的SOC估计
SOC estimation of power battery based on AUKF
摘要
Abstract
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.The AUKF is used in this model for online estimation of battery SOC in unknown noise environment.Experimental results show that the estimation error of UKF algorithm is beating between-0.04～0.06,while the estimation error of AUKF algorithm is kept within 0.05 and the SOC estimation error is corrected in real time.关键词
电动汽车/动力电池/SOC估计/自适应无迹卡尔曼滤波Key words
electric vehicle/power battery/SOC estimation/adaptive unscented Kalman filter分类
信息技术与安全科学引用本文复制引用
谢永东,何志刚,陈栋,周洪剑..自适应无迹卡尔曼滤波动力电池的SOC估计[J].北京交通大学学报,2018,42(2):129-137,9.基金项目
国家科技支撑计划项目(2015BAG07B00)National Key Technology Research and Development Program(2015BAG07B00) （2015BAG07B00）
