State of charge estimation of power Li-ion batteries using a hybrid estimation algorithm based on UKF

被引：52

作者：

He, Zhigang ^{[1
]}

Chen, Dong ^{[1
]}

Pan, Chaofeng ^{[1
,2
]}

Chen, Long ^{[1
,2
]}

Wang, Shaohua ^{[1
]}

机构：

[1] Jiangsu Univ, Coll Automobile & Traff Engn, Zhenjiang 212013, Jiangsu, Peoples R China

[2] Jiangsu Univ, Automot Engn Res Inst, Zhenjiang 212013, Jiangsu, Peoples R China

来源：

ELECTROCHIMICA ACTA | 2016年 / 211卷

基金：

中国国家自然科学基金;

关键词：

Electric vehicle; Power battery; State of charge; Unscented kalman filter; OPEN-CIRCUIT-VOLTAGE; LEAD-ACID-BATTERIES; OF-CHARGE; ELECTRIC VEHICLES; MANAGEMENT-SYSTEMS; LIFEPO4; BATTERIES; PARTICLE-FILTER; CELLS; PACKS;

D O I：

10.1016/j.electacta.2016.06.042

中图分类号：

O646 [电化学、电解、磁化学];

学科分类号：

081704 ;

摘要：

Based on the analysis of the existing State of charge (SOC) Estimation Algorithms of batteries, this paper proposes a hybrid estimation algorithm according to the UKF method, the Ah method and the open circuit method in SOC estimation of battery pack which consists of 320 batteries. The "buckets effect" exists between series batteries and the differences between each cell were also been taken into consideration during estimating the SOC of power batteries. Finally, the hybrid estimation algorithm was applied to estimate SOC of battery pack under ECE driving cycles. The result shows that the error of the hybrid estimation algorithm is less than 5%. (C) 2016 Elsevier Ltd. All rights reserved.

引用

页码：101 / 109

页数：9

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