State-of-charge estimation of lithium-ion battery pack by using an adaptive extended Kalman filter for electric vehicles

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作者信息关键词期刊信息基础信息归属信息摘要

成果类型：

期刊论文

作者：

Zhang, Zhiyong;Jiang, Li;Zhang, Liuzhu;Huang, Caixia

通讯作者：

Huang, Caixia(huanglq003@163.com)

作者机构：

[Jiang, Li; Zhang, Liuzhu; Zhang, Zhiyong] Changsha Univ Sci & Technol, Coll Automobile & Mech Engn, Changsha 410114, Peoples R China.

[Zhang, Zhiyong] Chongqing Univ Technol, Minist Educ, Key Lab Adv Manufacture Technol Automobile Parts, Chongqing 400054, Peoples R China.

[Huang, Caixia] Hunan Inst Engn, Hunan Prov Key Lab Vehicle Power & Transmiss Syst, Xiangtan 411104, Peoples R China.

通讯机构：

[Caixia Huang] H

Hunan Provincial Key Laboratory of Vehicle Power and Transmission System (Hunan Institute of Engineering), Xiangtan 411104, China

语种：

英文

关键词：

Adaptive filtering;Battery management systems;Battery Pack;Charging (batteries);Covariance matrix;Extended Kalman filters;Ions;Lithium-ion batteries;Numerical methods;Parameter estimation;Uncertainty analysis;Adaptive corrections;Adaptive extended Kalman filters;Battery pack;Ion batteries;Lithium ions;Model parameter identifications;Modeling parameters;Noise covariance matrix;State-of-charge estimation;Uncertainty;Electric vehicles

期刊：

Journal of Energy Storage

ISSN：

2352-152X

年：

2021

卷：

页码：

102457

DOI：

10.1016/j.est.2021.102457

基金类别：

This project is sponsored by the National Natural Science Foundation of China (No. 51675057 ), the Hunan Provincial Natural Science Foundation of China (No. 2020JJ4603 ), the Scientific Research Fund of Hunan Provincial Education Department (No. 20A018 ), and the Key Laboratory of Advanced Manufacture Technology for Automobile Parts, Ministry of Education (No. 2020KLMT03 ).

机构署名：

本校为第一机构

院系归属：

汽车与机械工程学院

摘要：

State-of-charge (SOC) estimation is an important aspect for modern battery management systems. Extended Kalman filter (EKF) has been extensively used in battery SOC estimation. However, EKF cannot obtain accurate estimation results when the model parameters have strong uncertainty or/and the accurate initial value of noise covariance matrix is unknown. To overcome these defects, the parameters of Lithium-ion battery model on the basis of the second-order resistor–capacitor (RC) equivalent model are identified, and then an improved adaptive EKF...

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State-of-charge estimation of lithium-ion battery pack by using an adaptive extended Kalman filter for electric vehicles

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