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

被引:173
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
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