In the multistage constant current (MSCC) charging process of lithium-ion batteries for electric vehicles (EVs), it is difficult to achieve coordinated optimization of MSCC based on charging time, charged electric quantity, and charging temperature rise. Therefore, in this study, the orthogonal experimental scheme is designed for multiobjective coordinated multistage current optimization, and a five-stage constant current (5SCC) optimization strategy is proposed according to the two orthogonal experiments. The comparative experimental results show that the battery can be charged from 20% state of charge (SOC) to 100% SOC using the proposed charging optimization strategy in about 30 min, and the maximum battery temperature (42.6 °C) is lower than the maximum allowable charge temperature (45 °C) during charging. Furthermore, the available capacity fading ratio of the proposed strategy is 1.81%, while that of the 1/3 C constant current and constant voltage (CC-CV) strategy is 1.65% after 60 cycle aging (CA) tests. In addition, the electrochemical impedance spectroscopy analysis of the batteries for the CA tests shows that the aging mechanism of the battery using the proposed strategy is consistent with that of the battery using the 1/3 C CC-CV charging strategy. Compared with the traditional CC-CV charging strategy, the proposed 5SCC charging strategy has good application prospects regarding charging time and charged electric quantity, and it can also be compared with the CC-CV charging strategy regarding battery aging. The research results can provide a reference for the optimization of the MSCC charging strategy for EVs.


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    Title :

    Multistage Constant Current Charging Strategy Based on Multiobjective Current Optimization


    Contributors:
    Wu, Xiaogang (author) / Xia, Yinlong (author) / Du, Jiuyu (author) / Gao, Xinjia (author) / Nikolay, Shchurov (author)


    Publication date :

    2023-12-01


    Size :

    3627136 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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