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An Optimal Fast-Charging Strategy for Lithium-Ion Batteries via an Electrochemical–Thermal Model with Intercalation-Induced Stresses and Film Growth

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  • Guangwei Chen

    (State Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027, China)

  • Zhitao Liu

    (State Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027, China)

  • Hongye Su

    (State Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027, China)

Abstract

Optimal fast charging is an important factor in battery management systems (BMS). Traditional charging strategies for lithium-ion batteries, such as the constant current–constant voltage (CC–CV) pattern, do not take capacity aging mechanisms into account, which are not only disadvantageous in the life-time usage of the batteries, but also unsafe. In this paper, we employ the dynamic optimization (DP) method to achieve the optimal charging current curve for a lithium-ion battery by introducing limits on the intercalation-induced stresses and the solid–liquid interface film growth based on an electrochemical–thermal model. Furthermore, the backstepping technique is utilized to control the temperature to avoid overheating. This paper concentrates on solving the issue of minimizing charging time in a given target State of Charge (SoC), while limiting the capacity loss caused by intercalation-induced stresses and film formation. The results indicate that the proposed optimal charging method in this paper offers a good compromise between the charging time and battery aging.

Suggested Citation

  • Guangwei Chen & Zhitao Liu & Hongye Su, 2020. "An Optimal Fast-Charging Strategy for Lithium-Ion Batteries via an Electrochemical–Thermal Model with Intercalation-Induced Stresses and Film Growth," Energies, MDPI, vol. 13(9), pages 1-16, May.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:9:p:2388-:d:356384
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    References listed on IDEAS

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    1. Abdel-Monem, Mohamed & Trad, Khiem & Omar, Noshin & Hegazy, Omar & Van den Bossche, Peter & Van Mierlo, Joeri, 2017. "Influence analysis of static and dynamic fast-charging current profiles on ageing performance of commercial lithium-ion batteries," Energy, Elsevier, vol. 120(C), pages 179-191.
    2. Dehghani-Sanij, A.R. & Tharumalingam, E. & Dusseault, M.B. & Fraser, R., 2019. "Study of energy storage systems and environmental challenges of batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 192-208.
    3. Muhammad Umair Ali & Sarvar Hussain Nengroo & Muhamad Adil Khan & Kamran Zeb & Muhammad Ahmad Kamran & Hee-Je Kim, 2018. "A Real-Time Simulink Interfaced Fast-Charging Methodology of Lithium-Ion Batteries under Temperature Feedback with Fuzzy Logic Control," Energies, MDPI, vol. 11(5), pages 1-15, May.
    4. Abdel Monem, Mohamed & Trad, Khiem & Omar, Noshin & Hegazy, Omar & Mantels, Bart & Mulder, Grietus & Van den Bossche, Peter & Van Mierlo, Joeri, 2015. "Lithium-ion batteries: Evaluation study of different charging methodologies based on aging process," Applied Energy, Elsevier, vol. 152(C), pages 143-155.
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    Cited by:

    1. Yong Li & Jue Yang & Wei Long Liu & Cheng Lin Liao, 2020. "Multi-Level Model Reduction and Data-Driven Identification of the Lithium-Ion Battery," Energies, MDPI, vol. 13(15), pages 1-23, July.
    2. Boshi Wang & Haitao Min & Weiyi Sun & Yuanbin Yu, 2021. "Research on Optimal Charging of Power Lithium-Ion Batteries in Wide Temperature Range Based on Variable Weighting Factors," Energies, MDPI, vol. 14(6), pages 1-21, March.

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