Electrochemical Estimation and Control for Lithium-Ion Battery Health-Aware Fast Charging

被引:171
|
作者
Zou, Changfu [1 ]
Hu, Xiaosong [2 ]
Wei, Zhongbao [3 ]
Wik, Torsten [1 ]
Egardt, Bo [1 ]
机构
[1] Chalmers Univ Technol, Dept Elect Engn, S-41296 Gothenburg, Sweden
[2] Chongqing Univ, Dept Automot Engn, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R China
[3] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore
关键词
Electrochemical model; fast charging; lithium-ion (Li-ion) battery; model predictive control (MPC); moving horizon estimation (MHE); state estimation; MODEL; STATE; OPTIMIZATION; MANAGEMENT; STRATEGY;
D O I
10.1109/TIE.2017.2772154
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Fast charging strategies have gained an increasing interest toward the convenience of battery applications but may unduly degrade or damage the batteries. To harness these competing objectives, including safety, lifetime, and charging time, this paper proposes a health-aware fast charging strategy synthesized from electrochemical system modeling and advanced control theory. The battery charging problem is formulated in a linear time-varying model predictive control algorithm. In this algorithm, a control-oriented electrochemical-thermal model is developed to predict the system dynamics. Constraints are explicitly imposed on physically meaningful state variables to protect the battery from hazardous operations. Amoving horizon estimation algorithm is employed to monitor battery internal state information. Illustrative results demonstrate that the proposed charging strategy is able to largely reduce the charging time from its benchmarks while ensuring the satisfaction of health-related constraints.
引用
收藏
页码:6635 / 6645
页数:11
相关论文
共 50 条
  • [21] State of health estimation of lithium-ion battery during fast charging process based on BiLSTM-Transformer
    Li, Ziyang
    Zhang, Xiangwen
    Gao, Wei
    ENERGY, 2024, 311
  • [22] A Numerical Study of Lithium-Ion Battery Fast Charging Behaviors
    Zhang, Sijie
    Zhao, Rui
    Gu, Junjie
    Liu, Jie
    2018 INTERNATIONAL CONFERENCE ON SENSING, DIAGNOSTICS, PROGNOSTICS, AND CONTROL (SDPC), 2018, : 449 - 454
  • [23] Silicon Anode: A Perspective on Fast Charging Lithium-Ion Battery
    Lee, Jun
    Oh, Gwangeon
    Jung, Ho-Young
    Hwang, Jang-Yeon
    INORGANICS, 2023, 11 (05)
  • [24] Machine learning-based lifelong estimation of lithium plating potential: A path to health-aware fastest battery charging
    Zhang, Yizhou
    Wik, Torsten
    Bergstrom, John
    Zou, Changfu
    ENERGY STORAGE MATERIALS, 2025, 74
  • [25] Practical State of Health Estimation of Lithium-ion Battery with High Robustness to Charging Partialness
    Ruan, Haokai
    He, Hongwen
    Wei, Zhongbao
    2021 IEEE TRANSPORTATION ELECTRIFICATION CONFERENCE & EXPO (ITEC), 2021,
  • [26] Fast Estimation of State of Charge for Lithium-ion Battery
    Chen, Hung-Cheng
    Chou, Shuo-Rong
    Chen, Hong-Chou
    Wu, Shing-Lih
    Chen, Liang-Rui
    2014 INTERNATIONAL SYMPOSIUM ON COMPUTER, CONSUMER AND CONTROL (IS3C 2014), 2014, : 284 - 287
  • [27] State of Health Estimation of Lithium-Ion Battery Based on Electrochemical Impedance Spectroscopy
    Fan, Maosong
    Geng, Mengmeng
    Yang, Kai
    Zhang, Mingjie
    Liu, Hao
    ENERGIES, 2023, 16 (08)
  • [28] An electrochemical-thermal model of lithium-ion battery and state of health estimation
    Wang, Dafang
    Zhang, Qi
    Huang, Huanqi
    Yang, Bowen
    Dong, Haosong
    Zhang, Jingming
    JOURNAL OF ENERGY STORAGE, 2022, 47
  • [29] Multi-zoned equivalent circuit modelling for health-aware battery fast charging optimization
    Bose, Bibaswan
    Garg, Akhil
    Gao, Liang
    2024 IEEE TRANSPORTATION ELECTRIFICATION CONFERENCE AND EXPO, ITEC 2024, 2024,
  • [30] Optimal Fast Charging Control for Lithium-ion Batteries
    Ouyang, Quan
    Ma, Rui
    Wu, Zhaoxiang
    Wang, Zhisheng
    IFAC PAPERSONLINE, 2020, 53 (02): : 12435 - 12439