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The integrated multi-performance fast optimization strategy for battery thermal management system

  • Hao Lu
  • , Xiaole Tang
  • , Hongchang Li
  • , Wenjun Zhao
  • , Xiqiang Chang
  • , Weifang Lin
  • Xinjiang University
  • Ltd.
  • State Grid Corporation of China

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Increased battery energy density is required to boost electric vehicle endurance; however, this also raises the possibility of thermal runaway and power battery explosion. Improving the cooling system performance requires optimization and enhancement of classical systems. Traditional design approaches struggle to simultaneously enhance multiple aspects of performance, while an optimization based on Computational Fluid Dynamics (CFD) methods is often inefficient. Therefore, by integrating a flow resistance network model (FRNM) with a weighted average optimization algorithm (INFO), an efficient optimization for the comprehensive performance of the system can be achieved. Five optimized systems under different airflow rates were obtained through optimization. A comparison with two existing systems validated the effectiveness of the optimized system. The results demonstrate that, compared to the two reference systems, the optimized system decreases the maximum temperature difference by 65.51 % and 39.07 %, respectively. Furthermore, the improvement in temperature uniformity is more significant, increasing by 63.76 % and 34.40 %, respectively.

Original languageEnglish
Article number103920
JournalCase Studies in Thermal Engineering
Volume54
DOIs
StatePublished - Feb 2024
Externally publishedYes

Keywords

  • Computational fluid dynamics
  • Optimization algorithm
  • Short-cut computation
  • Weighted average

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