中文核心期刊
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中国科技核心期刊
RCCSE中国核心学术期刊
重庆交通大学学报（自然科学版）

重庆交通大学学报（自然科学版） ›› 2022, Vol. 41 ›› Issue (09): 149-156.DOI: 10.3969/j.issn.1674-0696.2022.09.21

• 交通装备 • 上一篇    

锂离子电池复合热管理系统的多目标优化

张甫仁1，易孟斐1，汪鹏伟2，张林1,李世远1   

  1. (1. 重庆交通大学，机电与车辆工程学院，重庆400074； 2. 长城汽车股份有限公司，河北 保定 071000)
  • 收稿日期:2021-05-13 修回日期:2021-07-22 发布日期:2022-09-30
  • 作者简介:张甫仁（1975—），男，四川南充人，教授，博士，主要从事电池热管理方面的研究。E-mail:zh_feixue@163.com 通信作者：易孟斐（1997—），女，湖北黄冈人，硕士研究生，主要从事电池热管理方面的研究。E-mail:imengfei0330@126.com

Multi-objective Optimization of Composite Thermal Management System of Lithium-ion Battery

ZHANG Furen1, YI Mengfei1, WANG Pengwei2, ZHANG Lin1, LI Shiyuan1   

  1. (1. School of Mechatronics & Vehicle Engineering, Chongqing Jiaotong University, Chongqing 400074, China; 2. Great Wall Motor Co., Ltd., Baoding 071000, Hebei, China)
  • Received:2021-05-13 Revised:2021-07-22 Published:2022-09-30

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摘要： 为缓解锂离子电池组快速充放电时的严重积热，对传统U型、Z型并联风冷电池热管理系统（BTMS）进行优势整合，提出一种新型的I型BTMS（I-BTMS）。首先，进行了方形锂离子电池充放电实验，研究其不同倍率下的温升特性，以获得热物性参数，并且与电池的计算流体动力学(CFD)模型结果进行佐证。然后，基于验证后的CFD方法，发现在相同边界条件下I-BTMS的冷却效率比U-BTM、Z-BTMS更高。最后，通过添加风道隔板和微通道液冷板的风-液复合冷却方式对初始I-BTMS进行优化设计，将CFD方法和多目标优化相结合，对最优拉丁超立方抽样法获取的设计点进行数值计算，并且基于NSGA-Ⅱ遗传算法对系统冷却性能进行多目标寻优。迭代收敛的最优解显示，电池组的最高温和最大温差相比初始I-BTMS分别降低9.08%和70.19%。

关键词: 车辆工程；电池热管理；复合冷却；风冷；液冷；NSGA-Ⅱ遗传算法；多目标优化

Abstract: In order to alleviate the serious heat accumulation during rapid charge and discharge of lithium-ion battery pack, the advantages of traditional U-type and Z-type parallel air-cooled battery thermal management system (BTMS) were integrated, and a new I-type BTMS(I-BTMS) was proposed. Firstly, the charge and discharge experiments of square lithium-ion battery were carried out and the temperature rise characteristics at different rates were studied to obtain thermophysical parameters, which was verified with the results of the computational fluid dynamics (CFD) model of the battery. Then, based on the verified CFD method, it was found that the cooling efficiency of I-BTMS was higher than that of U-BTM and Z-BTMS under the same boundary conditions. Finally, the initial I-BTMS was optimized by air-liquid composite cooling mode with the addition of air duct partition and mini-channel liquid cooling plate. The design points obtained by the optimal Latin hypercube sampling were numerically calculated by combining CFD method with multi-objective optimization, and based on NSGA-Ⅱ genetic algorithm, the cooling performance of the system was optimized by multiple objectives. The optimal solution of iterative convergence shows that the maximum temperature and maximum temperature difference of the battery pack are reduced by 9.08% and 70.19%, respectively, compared with the initial I-BTMS.

Key words: vehicle engineering; battery thermal management; composite cooling; air cooling; liquid cooling; NSGA-Ⅱ genetic algorithm; multi-objective optimization

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