Design and optimization of 3D printed air-cooled heat sinks based on genetic algorithms
Design and optimization of 3D printed air-cooled heat sinks based on genetic algorithms
复制标题
基于遗传算法的3D打印风冷散热器设计与优化
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
S. Campbell
中科院分区：
文献类型：
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作者：
Tong Wu;B. Ozpineci;M. Chinthavali;Zhiqiang Wang;S. Debnath;S. Campbell
提高电力电子技术的功率密度和可靠性在电力电子应用中至关重要。设计过程中的关键挑战之一是设计最佳散热器。本文提出了一种基于遗传算法和有限元模拟相结合的风冷散热器设计方法。虽然GA在每次迭代中生成候选散热器的群体，但FEA模拟用于评估每个散热器的适应度函数。本文所考虑的适应度函数是半导体器件的最高结温。通过优选“适者生存”的方法，获得了提供比常规散热器更好的性能的散热器。文中还对优化后的风冷散热器进行了仿真和实验评估。
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.