Lithium-ion battery SOC estimation based on an improved adaptive extended Kalman filter

被引：5
|
作者：
Wang, Yunqiu [1 ]
Li, Lei [1 ]
Ding, Quansen [1 ]
Liu, Jiale [1 ]
Chen, Pengwei [1 ]
机构：
[1] Nanjing Univ Sci & Technol, Coll Automat, Nanjing, Peoples R China
来源：
PROCEEDINGS OF THE 2021 IEEE 16TH CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA 2021) | 2021年
关键词：
Lithium-ion battery; equivalent circuit model; SOC estimation; parameter identification; extended Kalman filter;
D O I：
10.1109/ICIEA51954.2021.9516403
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Battery is an important driving force of electric vehicles. Reasonable utilization of battery energy is a key link of battery management system. The battery management system can ensure the safety and efficiency of the battery by accurately estimating the SOC of the battery. In this paper, based on the establishment of battery equivalent model and parameter identification, a new battery SOC estimation method is proposed. This method is improved on the extended Kalman filter, and an adaptive filtering algorithm is used to solve the noise problem. Firstly, the theoretical analysis of the algorithm is completed. Finally, the simulation is carried out in MATLAB environment to verify the feasibility of the algorithm.
引用
收藏
页码：417 / 421
页数：5
相关论文
共 50 条
  • [31] SOC Estimation Method for Lithium-ion Batteries: Extended Kalman Filter with Weighted Innovation
    Han, Yiyang
    Ding, Jie
    Chen, Jiazhong
    Sun, Peng
    [J]. PROCEEDINGS OF THE 2019 31ST CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2019), 2019, : 5074 - 5078
  • [32] Adaptive extended kalman filter based fault detection and isolation for a lithium-ion battery pack
    He, Hongwen
    Liu, Zhentong
    Hua, Yin
    [J]. CLEAN, EFFICIENT AND AFFORDABLE ENERGY FOR A SUSTAINABLE FUTURE, 2015, 75 : 1950 - 1955
  • [33] Lithium-Ion Battery SOC Estimation Based on Adaptive Forgetting Factor Least Squares Online Identification and Unscented Kalman Filter
    Wang, Hao
    Zheng, Yanping
    Yu, Yang
    [J]. MATHEMATICS, 2021, 9 (15)
  • [34] Estimation of State of Charge for Lithium-Ion Battery Based on Finite Difference Extended Kalman Filter
    Cheng, Ze
    Lv, Jikao
    Liu, Yanli
    Yan, Zhihao
    [J]. JOURNAL OF APPLIED MATHEMATICS, 2014,
  • [35] The State of Charge Estimation of Lithium-Ion Battery Based on Temperature-Compensated Method with Adaptive Extended Kalman Filter
    Kung, Chung-Chun
    Liu, Sung-Hsun
    [J]. 2018 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2018, : 4144 - 4149
  • [36] Joint estimation of state of charge and state of health for lithium-ion battery based on dual adaptive extended Kalman filter
    Li, Jiabo
    Ye, Min
    Gao, Kangping
    Xu, Xinxin
    Wei, Meng
    Jiao, Shengjie
    [J]. INTERNATIONAL JOURNAL OF ENERGY RESEARCH, 2021, 45 (09) : 13307 - 13322
  • [37] Online state of charge estimation for the aerial lithium-ion battery packs based on the improved extended Kalman filter method
    Wang, Shunli
    Fernandez, Carlos
    Shang, Liping
    Li, Zhanfeng
    Li, Jianchao
    [J]. JOURNAL OF ENERGY STORAGE, 2017, 9 : 69 - 83
  • [38] SOC and SOH Joint Estimation of Lithium-Ion Battery Based on Improved Particle Filter Algorithm
    Wu, Tiezhou
    Liu, Sizhe
    Wang, Zhikun
    Huang, Yiheng
    [J]. JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, 2022, 17 (01) : 307 - 317
  • [39] SOC and SOH Joint Estimation of Lithium-Ion Battery Based on Improved Particle Filter Algorithm
    Tiezhou Wu
    Sizhe Liu
    Zhikun Wang
    Yiheng Huang
    [J]. Journal of Electrical Engineering & Technology, 2022, 17 : 307 - 317
  • [40] A hybrid Kalman filter for SOC estimation of lithium-ion batteries
    Hao, Tianyun
    Ding, Jie
    Tu, Taotao
    [J]. 2022 41ST CHINESE CONTROL CONFERENCE (CCC), 2022, : 5222 - 5227
12345