Temperature-aware charging strategy for lithium-ion batteries with adaptive current sequences in cold environments

Yongjie Liu, Zhiwu Huang, Liang He, Jianping Pan, Heng Li and Jun Peng

Applied Energy, 2023, vol. 352, issue C, No S0306261923013090

Abstract: This paper proposes a temperature-aware charging strategy with adaptive current sequences for lithium-ion batteries to improve their charging performance in cold environments, trading off between charging speed and the thus-caused capacity degradation. Specifically, a curved surface of the maximal allowed charging currents with different battery temperatures and states of charge (SoCs) is experimentally generated by using an integrated battery model that thoroughly describes temperature’s impacts on battery properties. Then, the commonly used multistage constant current charging scheme is improved by adapting the number of stages and associated transition conditions to battery temperature and SoC. The adaptive charging process enables batteries to self-heat quickly by applying a fast-increasing charging current sequence. Moreover, a balanced contour interval size of the curved surface is selected considering the fitness and computation time of the particle swarm optimization algorithm. Cycle charging tests are conducted with NCR18650B batteries. The results show that the proposed strategy can reduce the average charging time by 207–757 s, slow down the total capacity decay by 63–143 mAh over 20 charging cycles, and reduce the time for batteries to self-heat from −10 to 0 °C by over 500 s when compared with other existing charging methods.

Keywords: Lithium-ion battery; Cold environment; Temperature-aware charging; Adaptive current sequences; Optimal multiobjective charging; Battery self-heating (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.apenergy.2023.121945

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