Health-aware battery charging via iterative nonlinear optimal control syntheses

被引:4
|
作者
Minh Vu [1 ]
Zeng, Shen [1 ]
Fang, Huazhen [2 ]
机构
[1] Washington Univ, Dept Elect & Syst Engn, St Louis, MO 63130 USA
[2] Univ Kansas, Dept Mech Engn, Lawrence, KS 66045 USA
来源
IFAC PAPERSONLINE | 2020年 / 53卷 / 02期
关键词
Emerging applications in battery control; computational methods; MODEL-PREDICTIVE CONTROL; ION;
D O I
10.1016/j.ifacol.2020.12.1759
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
There is an increasing recognition of the critical importance of charging for the safety and life of lithium-ion batteries. This paper proposes a computationally efficient optimal control approach for the problem of real-time charging control. By incorporating specific constraints that must be satisfied during charging, a health-aware operation is promoted. To determine the optimal charging current in the given setup, a recently proposed iterative framework for solving constrained optimal control problems is leveraged. It is found that the resulting optimal charging currents can be expressed in terms of a piecewise-affine time-invariant state feedback law, which results in a high computational efficiency for the optimal control solution. Copyright (C) 2020 The Authors.
引用
收藏
页码:12485 / 12490
页数:6
相关论文
共 50 条
  • [1] Electrochemical Estimation and Control for Lithium-Ion Battery Health-Aware Fast Charging
    Zou, Changfu
    Hu, Xiaosong
    Wei, Zhongbao
    Wik, Torsten
    Egardt, Bo
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2018, 65 (08) : 6635 - 6645
  • [2] Actively temperature controlled health-aware fast charging method for lithium-ion battery using nonlinear model predictive control
    Yin, Yilin
    Choe, Song-Yul
    APPLIED ENERGY, 2020, 271
  • [3] A systematic approach for the parameter identification of electrochemical battery models enabling health-aware fast charging control of battery electric vehicles
    Wassiliadis, Nikolaos
    Ank, Manuel
    Bach, Andreas
    Wanzel, Matthias
    Zollner, Ann-Sophie
    Gamra, Kareem Abo
    Lienkamp, Markus
    Journal of Energy Storage, 2022, 56
  • [4] Development of Novel MSCCCTCV Charging Strategy for Health-Aware Battery Fast Charging Using QOGA Optimization
    Bose, Bibaswan
    Garg, Akhil
    Gao, Liang
    Kim, Jonghoon
    Singh, Surinder
    IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION, 2024, 10 (02): : 4432 - 4440
  • [5] A systematic approach for the parameter identification of electrochemical battery models enabling health-aware fast charging control of battery electric vehicles
    Wassiliadis, Nikolaos
    Ank, Manuel
    Bach, Andreas
    Wanzel, Matthias
    Zollner, Ann-Sophie
    Gamra, Kareem Abo
    Lienkamp, Markus
    JOURNAL OF ENERGY STORAGE, 2022, 56
  • [6] HEALTH-AWARE AND USER-INVOLVED BATTERY CHARGING MANAGEMENT FOR ELECTRIC VEHICLES USING LINEAR QUADRATIC CONTROL
    Fang, Huazhen
    Wang, Yebin
    PROCEEDINGS OF THE ASME 8TH ANNUAL DYNAMIC SYSTEMS AND CONTROL CONFERENCE, 2015, VOL 1, 2016,
  • [7] Optimal Health-aware Charging Protocol for Lithium-ion Batteries: A Fast Model Predictive Control Approach
    Torchio, M.
    Magni, L.
    Braatz, R. D.
    Raimondo, D. M.
    IFAC PAPERSONLINE, 2016, 49 (07): : 827 - 832
  • [8] Health-Aware Multiobjective Optimal Charging Strategy With Coupled Electrochemical-Thermal-Aging Model for Lithium-Ion Battery
    Gao, Yizhao
    Zhang, Xi
    Guo, Bangjun
    Zhu, Chong
    Wiedemann, Jochen
    Wang, Lin
    Cao, Jianhua
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2020, 16 (05) : 3417 - 3429
  • [9] 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,
  • [10] Health-Aware and User-Involved Battery Charging Management for Electric Vehicles: Linear Quadratic Strategies
    Fang, Huazhen
    Wang, Yebin
    Chen, Jian
    IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2017, 25 (03) : 911 - 923