[1]乔洁,谢肖肖,闫嘉诚,等.基于NSGA-Ⅱ的车用锂离子电池仿生叶脉液冷板优化设计[J].长安大学学报(自然科学版),2026,46(2):199-212.[doi:10.19721/j.cnki.1671-8879.2026.02.014]
　QIAO Jie,XIE Xiao-xiao,YAN Jia-cheng,et al.Optimization design of vehicular lithium-ion battery bionic leaf vein cold plate based on NSGA-Ⅱ[J].Journal of Chang’an University (Natural Science Edition),2026,46(2):199-212.[doi:10.19721/j.cnki.1671-8879.2026.02.014]
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基于NSGA-Ⅱ的车用锂离子电池仿生叶脉液冷板优化设计()
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长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
第46卷
期数:
2026年2期
页码:
199-212
栏目:
汽车与机械工程
出版日期:
2026-04-18

文章信息/Info

Title:
Optimization design of vehicular lithium-ion battery bionic leaf vein cold plate based on NSGA-Ⅱ
文章编号:
1671-8879(2026)02-0199-14
作者:
乔洁1; 谢肖肖1; 闫嘉诚1; 杨涵1; 2; 李峰3; 路畅4; 高强1*
(1. 长安大学 汽车学院,陕西 西安 710018; 2. 西北工业大学 动力与能源学院,陕西 西安 710129; 3. 比亚迪汽车销售有限公司,广东 深圳 518118; 4. 中国汽车工程研究院股份有限公司,重庆 401122)
Author(s):
QIAO Jie1;  XIE Xiao-xiao1;  YAN Jia-cheng1;  YANG Han1; 2;  LI Feng3;  LU Chang4;  GAO Qiang1*
(1. School of Automobile, Chang'an University, Xi'an 710018, Shaanxi, China; 2. School of Power and Energy, Northwestern Polytechnical University, Xi'an 710129, Shaanxi, China; 3. BYD Automobile Sales Co., Ltd., Shenzhen 518118, Guangdong, China; 4. China Automotive Engineering Research Institute Co., Ltd., Chongqing 401122, China)
关键词:
汽车工程;  电池热管理;  NSGA-Ⅱ;  仿生叶脉液冷板;  响应面代理模型;  熵权法
Keywords:
automotive engineering;  battery thermal management;  NSGA-Ⅱ;  bionic leaf-veined liquid cooling plate;  response surface surrogate model;  entropy weight method
分类号:
U464.93
DOI:
10.19721/j.cnki.1671-8879.2026.02.014
文献标志码:
A
摘要:
为提高车用锂离子电池热管理系统(BTMS)的冷却效能,实现结构参数的客观优化设计,提出一种仿生叶脉液冷板设计; 以冷却流道宽度、深度、夹角及冷却板壁厚为设计变量,以电池组最高温度、最大温差和平均温度为优化目标; 采用最优拉丁超立方采样(OLHS)生成28个样本点; 基于样本数据建立四阶响应面代理模型,并以决定系数和均方根误差评估模型精度; 运用第二代非支配排序遗传算法(NSGA-Ⅱ)对其结构参数进行多目标优化,获得帕累托前沿解集; 通过熵权法对各评价指标进行客观赋权,确定综合最优结构参数组合。研究结果表明:经NSGA-Ⅱ优化并结合熵权法筛选,得到最优结构参数,宽度为9 mm,深度为5 mm,夹角为46°、冷却板的壁厚为5 mm; 对比基础结构,经优化设计的液冷BTMS使电池组最高温度、最大温差和平均温度分别减小了0.55 ℃、1.14 ℃和0.59 ℃,且最大温差降幅达22.26%,冷却性能显著提升; 在不同放电倍率和乙二醇水溶液体积浓度下,优化后的液冷BTMS均展现最优冷却性能,放电倍率越高,降温效果越明显,整体冷却性能随乙二醇浓度升高略有下降,验证了优化算法的强鲁棒性; 所建立响应面模型预测精度较高,最高温度、最大温差及平均温度对应的均方根误差分别为0.063 ℃、0.069 ℃、0.055 ℃,均满足工程精度要求; 建立的仿生叶脉液冷板结构优化设计中,所采用的采样、建模及优化方法显著提升了液冷板冷却效能,且解决了最优解选择的主观干扰问题,具备较强的鲁棒性与工程应用价值。
Abstract:
To improve the cooling efficiency of vehicle lithium-ion battery thermal management system(BTMS)and realize the objective optimal design of structural parameters, a bionic leaf vein liquid cooling plate design was proposed. The width, depth, included angle of cooling channels and wall thickness of cooling plate were taken as design variables. The maximum temperature, maximum temperature difference and average temperature of battery pack were taken as optimization objectives. Optimal Latin hypercube sampling(OLHS)was adopted to generate 28 sample points. A fourth-order response surface surrogate model was established based on sample data. The model accuracy was evaluated by coefficient of determination and root mean square error. Non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)was used to conduct multi-objective optimization of its structural parameters. The Pareto frontier solution set was obtained. The entropy weight method was used to assign objective weight to each evaluation index. The comprehensive optimal combination of structural parameters was determined. The results show that the optimal structural parameters are obtained after NSGA-Ⅱ optimization and entropy weight method screening.The width is 9 mm, the depth is 5 mm, the included angle is 46°, and the wall thickness of cooling plate is 5 mm. Compared with the basic structure, the optimized liquid cooling BTMS reduces the maximum temperature, maximum temperature difference and average temperature of battery pack by 0.55 ℃, 1.14 ℃ and 0.59 ℃, respectively. The reduction rate of maximum temperature difference reaches 22.26%. The cooling performance is improved significantly. The optimized liquid cooling BTMS shows the optimal cooling performance under different discharge rates and volume concentrations of ethylene glycol aqueous solution. The cooling effect becomes more obvious with the increase of discharge rate. The overall cooling performance decreases slightly with the increase of ethylene glycol concentration. The strong robustness of the optimization algorithm is verified. The established response surface model has high prediction accuracy. The root mean square errors corresponding to the maximum temperature, maximum temperature difference and average temperature are 0.063 ℃, 0.069 ℃ and 0.055 ℃, respectively. All the errors meet the engineering accuracy requirements. In the established structural optimization design of bionic leaf vein liquid cooling plate, the adopted sampling, modeling and optimization methods significantly improve the cooling efficiency of liquid cooling plate. The problem of subjective interference in optimal solution selection is solved. The design has strong robustness and engineering application value. 6 tabs, 16 figs, 30 refs.

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备注/Memo

备注/Memo:
收稿日期:2025-08-03
基金项目:陕西省“两链”融合重点项目(2023JBGS-13); 咸阳市重大科技创新项目(L2025-ZDKJ-ZDGG-RGZN-003)
作者简介:乔 洁(1988-),女,陕西大荔人,高级工程师,工学博士,从事车辆性能测试、人车安全研究,E-mail:qiaojie@chd.edu.cn。
通信作者:高 强(1970-),男,甘肃兰州人,教授,工学博士,E-mail:gaoqiang@chd.edu.cn。
更新日期/Last Update: 2026-04-20