基于多目标优化的液冷板散热性能分析

doi:10.3969/j.issn.1674-8484.2024.06.012

摘要/Abstract

摘要：

为了提高冷却板的冷却性能和解决压力损失大的问题，采用一种复合 X 型通道液冷板结构来研究锂离子电池的散热性能。以通道倾斜角、通道位置及入口通道上下夹角为设计变量，通过目标函数（平均温度、温度标准差、压降）得到液冷板的综合冷却性能，进而确定液冷板的最优结构参数；通过单体电池实验，得到电池在不同放电倍率下的产热量及温升特性；采用 Latin 超立方体（LHS）在设计空间内抽取 70 组样本点，基于近似模型（RSA）建立设计变量与目标函数之间的关系，采用非支配排序遗传算法Ⅱ（NSGA-Ⅱ）对RSA进行寻优，利用计算流体力学（CFD）验证寻优结果的合理性。结果表明：液冷板的泵送功率得到有效改善，与初始模型相比，压降降低了37.9%，综合冷却性能提升了 55.3%。

关键词: 锂离子电池, 电池热管理系统（BTMS）, 液体冷却, 多目标优化, 压力损失

Abstract:

In order to improve the cooling performance of the cooling plate and solve the problem of high pressure loss, a composite X-channel liquid cooling plate structure was used to study the heat dissipation performance of lithium-ion battery. By considering the channel inclination angle, channel position, and inlet channel angle as design variables, the comprehensive cooling performance of the liquid-cooled plate was evaluated using an objective function that included average temperature, temperature standard deviation, and pressure drop. Subsequently, the optimal structural parameters of the liquid-cooled plate were determined. The heat production and temperature rise characteristics of the battery under different discharge multipliers were obtained through single-cell experiments. The thermal generation and temperature increase characteristics of the battery at various discharge rates were determined through experiments conducted on a single cell. Latin Hypercube Sampling (LHS) was employed to select 70 sample points within the design space. An approximate model, specifically Response Surface Approximation (RSA), was then utilized to establish the relationship between the design variables and the objective function. The RSA model was subsequently optimized using the Non-Dominated Sorting Genetic Algorithm Ⅱ (NSGA-Ⅱ), and the validity of the optimization outcomes was confirmed via Computational Fluid Dynamics (CFD) simulations. The results show that the pumping power of the liquid cooling plate is effectively improved, the pressure drop is reduced by 37.865%, and the overall cooling performance is increased by 55.3% compared with the initial model.

Key words: lithium-ion battery, battery thermal management system(BTMS), liquid cooling, multi-objective optimization, pressure loss

中图分类号:

邱帅帅, 张甫仁, 孙世政, 陶远兵, 陶佳辉, 谭海坤. 基于多目标优化的液冷板散热性能分析[J]. 汽车安全与节能学报, 2024, 15(6): 905-914.

QIU Shuaishuai, ZHANG Furen, SUN Shizheng, TAO Yuanbing, TAO Jiahui, TAN Haikun. Analysis of heat dissipation performance of liquid cooling plate based on multi-objective optimization[J]. Journal of Automotive Safety and Energy, 2024, 15(6): 905-914.

图/表 21

参考文献 23

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D₁/ mm	D₂/ mm	D₃~ D₆/ mm	D₇、D₈/ mm	D₉/ mm
140	65	4	1	4
H₁/ mm	H₂/ mm	α / (°)	β / (°)
4	1	20	30

D₁/ mm	D₂/ mm	D₃~ D₆/ mm	D₇、D₈/ mm	D₉/ mm
140	65	4	1	4
H₁/ mm	H₂/ mm	α / (°)	β / (°)
4	1	20	30

放电倍率 / C	产热量 / (W·m^-3)	热通量 / (W·m^-3)
1	15 935	287
2	42 858	771
3	80 769	1 454
4	129 670	2 334
5	189 560	3 412

放电倍率 / C	产热量 / (W·m^-3)	热通量 / (W·m^-3)
1	15 935	287
2	42 858	771
3	80 769	1 454
4	129 670	2 334
5	189 560	3 412

范围	设计变量
范围	a / mm	b / mm	α / (°)	β / (°)	θ / (°)
下限	7	21	17	26	45
上限	17.5	42	24	50	90