Thermal management plays a vital role in ensuring that each single cell in the battery pack works within a reasonable temperature range while maintaining the temperature uniformity among the cells and battery modules in the pack as much as possible. In this study, an electrochemical–thermal model coupled to conjugate heat transfer and fluid dynamics simulations is utilized to accurately evaluate the thermal behavior of the battery pack. The effect of different cooling structures, the number of mini-channels, and the inlet mass flow rate on the temperature indexes of the battery pack are investigated by single-factor analysis method. Then, the simple and efficient orthogonal analysis and comprehensive analysis are used to obtain the optimal factor combination. Results show that the cooling structure design significantly affects the area where the highest temperature occurs in the battery pack. Meanwhile, case D can obviously improve the temperature indexes of the battery pack. The maximum temperature of the battery pack decreases as the number of mini-channels increases, but the downward trend decreases. On the basis of aforementioned work, the optimal combination can control the maximum temperature below 302 K and reduce the maximum temperature difference to 3.52 K. The research and optimization strategies in this paper can provide promising optimization solutions for battery thermal management systems.

热管理在确保电池组中的每个单节电池在合理的温度范围内工作的同时，尽可能地保持电池组中的电池组和电池模块之间的温度均匀性起着至关重要的作用。在这项研究中，结合了共轭传热和流体动力学模拟的电化学-热模型被用来准确评估电池组的热性能。采用单因素分析方法研究了不同的冷却结构，微通道数量和进气质量流量对电池组温度指标的影响。然后，使用简单有效的正交分析和综合分析来获得最佳因子组合。结果表明，冷却结构设计显着影响了电池组中温度最高的区域。同时，情况D可以明显改善电池组的温度指数。电池组的最高温度随着微型通道数量的增加而降低，但下降趋势却减小。在上述工作的基础上，最优组合可以将最高温度控制在302 K以下，并将最大温度差减小到3.52K。本文的研究和优化策略可以为电池热管理系统提供有希望的优化解决方案。电池组的最高温度随着微型通道数量的增加而降低，但下降趋势却减小。在上述工作的基础上，最优组合可以将最高温度控制在302 K以下，并将最大温度差减小到3.52K。本文的研究和优化策略可以为电池热管理系统提供有希望的优化解决方案。电池组的最高温度随着微型通道数量的增加而降低，但下降趋势却减小。在上述工作的基础上，最优组合可以将最高温度控制在302 K以下，并将最大温度差减小到3.52K。本文的研究和优化策略可以为电池热管理系统提供有希望的优化解决方案。