Optimization and analysis of maximum temperature in a battery pack affected by low to high Prandtl number coolants using response surface methodology and particle swarm optimization algorithm

Abstract

Thermal analysis of heat-generating battery pack cooled by several coolants is analyzed numerically. The coolant used are gases, oils, thermal oils, nanofluids, and liquid metals to find the best coolant for temperature distribution. The conductivity ratio between the battery and coolant, flow Reynolds number, and heat generation inside the pack is varied for each coolant. The axial temperature variation, which provides the location and magnitude of maximum temperature, is studied. The maximum temperature of the battery pack is analyzed using response surface methodology, optimization of maximum temperature is performed using particle swarm optimization algorithm, and regression analysis is carried out at the end of this work. The thermal analysis carried out reveals that the gas coolants are inefficient in providing lower temperatures while nanofluids are most suitable. The response surface reveals that the maximum temperature behavior is different for each category of coolant.