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《工程(英文)》 >> 2021年 第7卷 第8期 doi: 10.1016/j.eng.2020.06.016

基于液冷的电池热管理系统快充-冷却耦合规划方法

a State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
b Intelligent Manufacturing Key Laboratory of Ministry of Education, Shantou University, Shantou 515063, China

收稿日期: 2020-01-20 修回日期: 2020-05-17 录用日期: 2020-06-02 发布日期: 2020-07-30

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摘要

高效的快速充电技术对电动汽车行驶里程的拓展十分重要。然而,锂离子电池在大电流充电倍率下会大量产热。为解决这一问题,急需一种高效的快速充电-冷却规划方法。此次研究针对锂离子电池组的快速充电过程,设计了一种配有微流道的基于液冷的热管理系统。基于81组实验数据,提出了一种基于神经网络的回归模型,由三个考虑以下输出的子模型构成:最高温度、温度标准差及功耗。训练后的子模型均呈现出较高的测试准确性(99.353%、97.332%和98.381%)。此回归模型用于预测一个设计方案全集的三个输出参数,此全集由不同充电阶段的充电电流倍率[0.5C、1C、1.5C、2C和2.5C(1C = 5 A)],以及不同的冷却液流量(0.0006 kg·s-1、0.0012 kg·s-1和0.0018 kg·s-1)组成。最终从预测得到的设计方案全集中筛选出一组最优过程方案,并经实验得到了验证。结果表明在功耗低于0.02 J的情况下电池组荷电状态(SOC)值经15 min充电后增长了0.5。同时最高温度和温度标准差可分别控制在33.35 ℃和0.8 ℃以内。本文所提出的方法可供电动汽车行业在实际快速充电工况下使用。此外,可以基于实验数据预测最佳快速充电-冷却计划,从而显著提高充电过程设计的效率,并控制冷却过程中的能耗。

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