Health-Aware Multiobjective Optimal Charging Strategy With Coupled Electrochemical-Thermal-Aging Model for Lithium-Ion Battery

• Published in: IEEE transactions on industrial informatics Vol. 16; no. 5; pp. 3417 - 3429
• Main Authors: Gao, Yizhao, Zhang, Xi, Guo, Bangjun, Zhu, Chong, Wiedemann, Jochen, Wang, Lin, Cao, Jianhua
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.05.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Aging; Algorithms; Batteries; Battery degradation; Charging; Constraint modelling; Degradation; electrochemical-thermal-aging model; Electrodes; Electrolytes; Health; health-aware optimal charge; Lithium; lithium plating; lithium-ion (Li-ion) battery; Lithium-ion batteries; Mathematical model; multiobjective; Multiple objective analysis; Rechargeable batteries; solid-electrolyte-interphase (SEI) growth; Solids; State variable; temperature rise
• ISSN: 1551-3203; 1941-0050
• DOI: 10.1109/TII.2019.2935326

Battery 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, lifespan, and charging time, in this article, we propose a novel health-aware multiobjective optimal charging strategy to simultaneously shorten the charging time and relieve the battery degradation. The multiobjective optimal charging problem is formulated based on a coupled electrochemical-thermal-aging battery model. Constraints are explicitly imposed on physically meaningful state variables to avoid hazardous operations. Charging duration and battery aging process are well traded-off. Strategies for minimum-time and health-aware fast charging are investigated using different input current bounds, subject to both side reaction and temperature constraints. The experimental results validate that the presented multiobjective health-aware optimal charging algorithm is capable of reducing the charging time from its benchmarks largely without sacrificing the state-of-health of the battery.