中国机械工程Issue(3)：394-397,4.DOI:10.3969/j.issn.1004132X.2015.03.019
基于扩展卡尔曼粒子滤波算法的锂电池 SOC 估计
SOC Estimation for Li-Ion Battery Based on Extended Kalman Particle Filter
摘要
Abstract
scribed the residual capacity,and indicated the remainder driving range of electric vehicles.The cycles, As the key parameter for power battery management,the SOC of Li-ion battery de-instantaneous high current,abnormal temperatures and other factors would change cell characteristics, which might introduce larger errors even divergence over time if the extended Kalman filter algorithm were applied to the SOC estimation.To suppress the divergence and noise,this paper proposed a meth-od based on EKPF algorithm to realize accurate SOC and the current drift estimation on the Li-ion battery mixed noise model.Finally,the superiority of this method was validated by simulation results.关键词
锂电池/荷电状态/混合噪声模型/扩展卡尔曼粒子滤波Key words
L-i ion battery/state-of-charge(SOC)/mixed noise model/extended Kalman particle fil- ter(EKPF)分类
交通工程引用本文复制引用
赵又群,周晓凤,刘英杰..基于扩展卡尔曼粒子滤波算法的锂电池 SOC 估计[J].中国机械工程,2015,(3):394-397,4.基金项目
国家高技术研究发展计划(863计划)资助项目(2011AA11A210,2011AA11A220) （863计划）
