An unscented kalman filtering method for estimation of state-of-charge of lithium-ion battery

被引：8
作者：
Guo, Jishu [1 ]
Liu, Shulin [2 ]
Zhu, Rui [3 ]
机构：
[1] Qilu Univ Technol, Shandong Acad Sci, Sch Informat & Automat Engn, Jinan, Peoples R China
[2] Linyi Univ, Sch Automat & Elect Engn, Linyi, Peoples R China
[3] Shandong Normal Univ, Sch Informat Sci & Engn, Jinan, Peoples R China
来源：
FRONTIERS IN ENERGY RESEARCH | 2023年 / 10卷
关键词：
EKF; UKF; SOC estimation; lithium-ion battery; model; SOC ESTIMATION;
D O I：
10.3389/fenrg.2022.998002
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 estimation of battery state of charge (SOC) is of great significance to improve battery management and service life. An unscented Kalman filter (UKF) method is used to increase the accuracy of SOC estimation in this paper. Firstly, a battery model that the parameters are identified by using the least squares algorithm is established, which is foundation of the two-order RC equivalent circuit model. Secondly, SOC is estimated by UKF. In order to validate the method, experiments have been carried out under different operating conditions for LiFePO4 batteries. The obtained results are compared with that of the extended Kalman filter. Finally, the comparison shows that the UKF method provides better accuracy in the battery SOC estimation. Its estimation error is less than 2%, which is better than EKF algorithm. An effective method is provided for state estimation for battery management system.
引用
收藏
页数：9
相关论文
共 50 条
[41]   State-of-charge estimation and uncertainty for lithium-ion battery strings [J].
Truchot, Cyril ;
Dubarry, Matthieu ;
Liaw, Bor Yann .
APPLIED ENERGY, 2014, 119 :218-227
[42]   State-of-Charge Estimation Method for Lithium-Ion Batteries Using Extended Kalman Filter With Adaptive Battery Parameters [J].
Yun, Jaejung ;
Choi, Yeonho ;
Lee, Jaehyung ;
Choi, Seonggon ;
Shin, Changseop .
IEEE ACCESS, 2023, 11 :90901-90915
[43]   An Adaptive Unscented Kalman Filtering Approach for Online Estimation of Model Parameters and State-of-Charge of Lithium-Ion Batteries for Autonomous Mobile Robots [J].
Partovibakhsh, Maral ;
Liu, Guangjun .
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2015, 23 (01) :357-363
[44]   A Novel Adaptive Back Propagation Neural Network-Unscented Kalman Filtering Algorithm for Accurate Lithium-Ion Battery State of Charge Estimation [J].
Wang, Yangtao ;
Wang, Shunli ;
Fan, Yongcun ;
Xie, Yanxin ;
Fernandez, Carlos .
METALS, 2022, 12 (08)
[45]   State-of-Charge Estimation of Lithium-Ion Battery Using Square Root Spherical Unscented Kalman Filter (Sqrt-UKFST) in Nanosatellite [J].
Aung, Htet ;
Low, Kay Soon ;
Goh, Shu Ting .
IEEE TRANSACTIONS ON POWER ELECTRONICS, 2015, 30 (09) :4774-4783
[46]   Lithium-ion Battery State of Charge Estimation Model Based on Kalman Filtering Algorithm and Equivalent Circuit [J].
Wang, Xiao-Tian ;
Zhang, Ze-Zheng ;
Wang, Jie-Sheng ;
Zhang, Song-Bo ;
Liu, Xun .
ENGINEERING LETTERS, 2024, 32 (07) :1266-1274
[47]   Lithium-ion battery state of charge estimation based on square-root unscented Kalman filter [J].
Gholizade-Narm, Hossein ;
Charkhgard, Mohammad .
IET POWER ELECTRONICS, 2013, 6 (09) :1833-1841
[48]   A Novel Square Root Adaptive Unscented Kalman Filter Combined with Variable Forgetting Factor Recursive Least Square Method for Accurate State-of-charge Estimation of Lithium-Ion Batteries [J].
Zhang, Mengyun ;
Wang, Shunli ;
Yang, Xiao ;
Xu, Wenhua ;
Yang, Xiaoyong ;
Fernandez, Carlos .
INTERNATIONAL JOURNAL OF ELECTROCHEMICAL SCIENCE, 2022, 17 (09)
[49]   State of Charge and parameters estimation for Lithium-ion battery using Dual Adaptive Unscented Kalman Filter [J].
Guo, Hongzhen ;
Wang, Zhonghua ;
Li, Yueyang ;
Wang, Dongxue ;
Wang, Guangying .
2017 29TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2017, :4962-4966
[50]   State-of-charge estimation of lithium-ion battery pack by using an adaptive extended Kalman filter for electric vehicles [J].
Zhang, Zhiyong ;
Jiang, Li ;
Zhang, Liuzhu ;
Huang, Caixia .
JOURNAL OF ENERGY STORAGE, 2021, 37
12345