A New Model-Based Lithium-Ion Battery Online Monitoring Structure

被引：2

作者：

Meng, Jianwen ^{[1
,2
]}

Boukhnifer, Moussa ^{[1
]}

Diallo, Demba ^{[2
,3
]}

机构：

[1] Ecole Ingenieurs, ESTACA, 12 Ave Paul Delouvrier, F-78066 St Quentin En Yvelines, France

[2] Univ Paris Sud, Univ Paris Saclay, Sorbonne Univ, GeePs Grp Elect Engn Paris,CNRS,Cent Supelec, 3 & 11 Rue Joliot Curie, F-91192 Gif Sur Yvette, France

[3] Shanghai Maritime Univ, Shanghai 201306, Peoples R China

来源：

2019 PROGNOSTICS AND SYSTEM HEALTH MANAGEMENT CONFERENCE (PHM-PARIS) | 2019年

关键词：

Lithium-Ion battery; equivalent circuit model; Luenberger observer; Kalman filtering; STATE-OF-CHARGE; MANAGEMENT-SYSTEMS; PARAMETERS; HEALTH; PACKS;

D O I：

10.1109/PHM-Paris.2019.00012

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Based on the extended battery equivalent circuit model (ECM), joint and dual estimation frameworks are extensively used to execute the online battery monitoring. Although various observers are applied in these classical estimation frameworks to improve the monitoring result, the essence of the classical frameworks has not been changed. Therefore, a new online battery monitoring structure that still based on the extended ECM is proposed in this paper. Commonly used observers, namely, extended Kalman filter (EKF), unscented Kalman filter (UKF) and Luenberger observer (LO), are selected and employed for it. Apart from providing a simultaneous estimation of battery open-circuit-voltage (OCV), more rapid and more stable battery capacity estimation are the main advantages of the new proposed monitoring structure. Besides, comparative simulation studies have verified its effectiveness.

引用

页码：24 / 29

页数：6

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