4.7 Article

Effect analysis on performance enhancement of a novel air cooling battery thermal management system with spoilers

期刊

APPLIED THERMAL ENGINEERING
卷 192, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.applthermaleng.2021.116932

关键词

Battery thermal management system; Air cooling; Spoiler; Genetic programming model

资金

  1. China Postdoctoral Science Foundation [2020M683237]
  2. Special Funding for Postdoctoral Research Projects in Chongqing [XmT2020115]
  3. Science and Technology Innovation Project of Chengdu-Chongqing Double City Economic Circle Construction [KJCXZD2020013]
  4. Chongqing Technology Innovation and Application Program [cstc2020jscx-msxmX0202]

向作者/读者索取更多资源

This study introduces a novel air cooling BTMS to improve heat dissipation by installing spoilers in the battery gap, reducing maximum temperature and volume. By combining CFD simulation with a multi-objective genetic algorithm, the optimization results show reductions in both maximum temperature and BTMS volume, providing guidance for improving heat dissipation and cost savings in the industry.
To solve a series of thermal runaway problems caused by temperature and the cost problem caused by the excessive volume of the battery thermal management system (BTMS), this paper presents a novel air cooling BTMS which reduces the temperature and volume. In this study, we install the spoilers in the battery gap spacing, which can effectively improve the heat dissipation performance of the battery. Firstly, this paper discusses the influence of the shape, number and length of the spoilers on the maximum temperature (Max(T)) and temperature uniformity of the battery module. After computational fluid dynamics (CFD) simulation, this paper takes a BTMS with 16 long straight spoilers as plan 1. Compared with the initial plan without spoilers, the Max(T) of plan 1 is reduced by 3.52 K. Secondly, Latin hypercube sampling (LHS) is used to sample and then establish the genetic programming (GP) model for the Max(T) and the volume of plan 1. Finally, this paper combines CFD simulation with the multi-objective genetic algorithm (MOGA) to drive the optimization process. The optimization results show that the Max(T) of the battery module is 307.58 K, and the volume of BTMS is 12644460 mm(3). Compared with plan 1, the Max(T) is reduced by 2.24 K, and the volume is reduced by 4.87%. This result has guiding significance for improving the heat dissipation of Z-shaped air cooling BTMS and saving the cost in the industry.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据