Multi-objective optimization of heat transfer performance of power battery cold plate based on bionic spider web flow channel

With the rapid advancement of new energy vehicles, effective thermal management of power batteries has become increasingly critical. This study presents a comprehensive numerical investigation using Computational Fluid Dynamics (CFD) to develop an innovative bionic spider web-inspired liquid cooling system enhanced with nanofluids. We establish a sophisticated physical model to analyze the thermal performance by systematically optimizing three key parameters: nanofluid inlet temperature, copper nanoparticle volume fraction, and flow velocity. Our comprehensive multi-parameter optimization using Response Surface Method (RSM) revealed that a 5% copper nanoparticle concentration achieves optimal cooling, reducing average and maximum battery temperatures by 0.68% and 0.67% respectively, while maintaining a manageable 16.85% increase in pressure drop. The study further identifies the most efficient operating conditions as 1.896% nanoparticle volume fraction, 283K inlet temperature, and 0.05 m/s flow velocity, establishing an optimal balance between cooling efficiency and system energy consumption. These findings provide valuable insights for the design of high-performance thermal management systems in electric vehicles, offering a scientifically validated solution that enhances both cooling effectiveness and operational efficiency.