Lithium-ion battery SOC estimation study based on Cubature Kalman filter

被引:34
作者
Luo, Jiayi [1 ]
Peng, Jiankun [1 ,2 ]
He, Hongwen [1 ,2 ]
机构
[1] Beijing Inst Technol, Natl Engn Lab Elect Cehicles, Beijing 100081, Peoples R China
[2] Beijing Inst Technol, Collaborat Innovat Ctr Elect Vehicles Beijing, Beijing 100081, Peoples R China
来源
INNOVATIVE SOLUTIONS FOR ENERGY TRANSITIONS | 2019年 / 158卷
基金
中国国家自然科学基金;
关键词
Cubature Kalman Filter (CKF); Equivalent Circuit Model; Fractional Order Model; State of Charge; Lithium-ion battery;
D O I
10.1016/j.egypro.2019.01.933
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
In this paper, a state of charge (SOC) estimation method of Lithium-Ion battery is developed based on a cubature Kalman filter (CKF) supported by experimental data. Firstly, an equivalent circuit model and a fractional order model are established to evaluate the estimation accuracy of different models. Secondly, model parameters are identified through HPPC (Hybrid Pulse Power Characteristic) experiments based on the Sequential Quadratic Programming (SQR) method. Then, a CKF algorithm is used to eliminate the battery SOC under different battery models with no prior knowledge of initial SOC. The experimental results show that the proposed method can estimate the battery SOC with high accuracy and the fractional order model can achieve higher accuracy while it consumes more computing resources compared with EKF (Extended Kalman filter) algorithm. (C) 2019 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:3421 / 3426
页数:6
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