散热片
结温
逆变器
半导体器件
有限元法
机械工程
适应度函数
电子工程
可靠性(半导体)
功率(物理)
工程类
汽车工程
计算机科学
材料科学
遗传算法
电气工程
结构工程
物理
电压
复合材料
机器学习
量子力学
图层(电子)
作者
Tong Wu,Zhiqiang Wang,Burak Ozpineci,Madhu Chinthavali,Steven Campbell
出处
期刊:IEEE Transactions on Power Electronics
[Institute of Electrical and Electronics Engineers]
日期:2018-11-20
卷期号:34 (6): 5027-5031
被引量:51
标识
DOI:10.1109/tpel.2018.2881454
摘要
Heatsink design is critical for power density and reliability enhancement of power semiconductor modules. In this letter, an automated design and optimization methodology for air-cooled heatsinks are proposed based on genetic algorithm and finite element analysis. While the genetic algorithm generates a population of candidates with complex heatsink cross-section geometry in each iteration, finite element analysis is used to evaluate the fitness function of individual heatsink, i.e., junction temperature of semiconductor devices. With the rule of “survival of the fittest,” the proposed methodology eventually converges to an optimum heatsink design with the lowest device junction temperature. The optimized heatsink is fabricated through three-dimensional printing technology for thermal performance evaluation. Simulation and experimental evaluations have been conducted based on a 50-kW three-phase air-cooled inverter with the fabricated heatsinks. The comparative evaluation results show that the optimized heatsink is superior over a customized solution by 27% less in size and 6% lower in junction temperature.
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