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

• DOI: 10.1016/j.csite.2023.103920
• Publication Date: 2024-01-18T20:11:00Z
• Authors: Hao Lu; Xiaole Tang; Hongchang Li; Wenjun Zhao; Xiqiang Chang; Weifang Lin
• Keywords: System optimization; Performance Improvement

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