2021 IEEE International Conference on Mechatronics and Automation (ICMA) | 2021
Optimization of Pin Arrangement and Geometry in EV and HEV Heat Sink Using Genetic Algorithm Coupled With CFD
Abstract
The development of high-power electronic devices applied to various energy systems has recently gained a great deal of attention and specifically for electric vehicles (EVs) or hybrid electric vehicles (HEVs). However, the continued miniaturization and increased power output of power electronic have also introduced several design challenges especially in thermal management. In this paper, a genetic algorithm (GA) is used as a design tool to optimize both the pin arrangement and pin geometry of a pin fin heat sink with localized heat sources representing an EV power driver. Computational fluid dynamics (CFD) simulation is used in the GA to evaluate the performance of each potential design during optimization. The GA optimizes a performance index which captures both the pressure drop across the heat exchanger and the thermal efficiency with the two conflicting objectives, the Colburn factor $j$ and the friction factor f. A sets of optimization with different geometric parameters have been carried out and compared. The results demonstrate that GA coupled with CFD may be used to create designs that have better heat transfer coefficient and less pressure requirement than traditional pin fin arrangement designs.