电池(电)
充电周期
锂离子电池
粒子群优化
涓流充电
汽车工程
荷电状态
恒流
锂(药物)
计算机科学
电流(流体)
模拟
电气工程
工程类
算法
功率(物理)
医学
物理
量子力学
内分泌学
作者
Yongjie Liu,Zhiwu Huang,Liang He,Jianping Pan,Heng Li,Jun Peng
出处
期刊:Applied Energy
[Elsevier BV]
日期:2023-09-22
卷期号:352: 121945-121945
被引量:3
标识
DOI:10.1016/j.apenergy.2023.121945
摘要
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.
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