Design and optimization of 3D printed air-cooled heat sinks based on genetic algorithms

摘要

Enhancing power density and reliability of power electronics is extremely important in power electronics applications. One of the key challenges in the design process is to design the optimum heat sink. In this paper, an algorithm is proposed to design air-cooled heat sinks using genetic algorithm (GA) and finite element analysis (FEA) simulations. While the GA generates a population of candidate heat sinks in each iteration, FEA simulations are used to evaluate the fitness function of each. The fitness function considered in this paper is the maximum junction temperature of the semiconductor devices. With an approach that prefers “survival of the fittest”, a heat sink providing better performance than the conventional heat sinks is obtained. The simulation and experimental evaluations of the optimized air-cooled heat sink are also included in the paper.