A novel multi-model probability based battery state-of-charge fusion estimation approach

被引:4
|
作者
Mu, Hao [1 ]
Xiong, Rui [1 ]
Sun, Fengchun [1 ]
机构
[1] Beijing Inst Technol, Sch Mech Engn, Collaborat Innovat Ctr Elect Vehicles Beijing, 5 South Zhongguancun St, Beijing 100081, Peoples R China
关键词
Electric vehicles; batteries; state estimation; multi-model probability; H infinity;
D O I
10.1016/j.egypro.2016.06.061
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
Accurate state of charge (SoC) estimation is very important for managing battery with safety and efficiency. In order to improve the reliability and redundancy of the SoC estimation, the multi-model probability fusion estimation (MMPFE) method is presented. Considering that the estimation results being dependent on models, the MMPFE method is utilized to fuse the SoC results gained by different equivalent circuit models (ECMs). LFP type battery are tested to verify the effectiveness of the method. Results indicate that the proposed approach can achieve accurate battery SoC estimation with good robust and reliability. (C) 2016 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:840 / 846
页数:7
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