Automated Heatsink Optimization for Air-Cooled Power Semiconductor Modules

Tong Wu; Zhiqiang Wang; Burak Ozpineci; Madhu Chinthavali; Steven Campbell

doi:10.1109/TPEL.2018.2881454

Automated Heatsink Optimization for Air-Cooled Power Semiconductor Modules

Tong Wu, Zhiqiang Wang, Burak Ozpineci, Madhu Chinthavali, Steven Campbell

Research output: Contribution to journal › Article › peer-review

52 Scopus citations

Abstract

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.

Original language	English
Article number	8536448
Pages (from-to)	5027-5031
Number of pages	5
Journal	IEEE Transactions on Power Electronics
Volume	34
Issue number	6
DOIs	https://doi.org/10.1109/TPEL.2018.2881454
State	Published - Jun 2019

Funding

This work was supported by the SunShot National Laboratory Multiyear Partnership program, Department of Energy Solar Energy Technologies Office, under a contract with UT Battelle, LLC. Manuscript received September 25, 2018; revised October 26, 2018; accepted November 10, 2018. Date of publication November 15, 2018; date of current version April 20, 2019. This work was supported by the SunShot National Laboratory Multiyear Partnership program, Department of Energy Solar Energy Technologies Office, under a contract with UT Battelle, LLC. (Corresponding author: Zhiqiang Wang.) T. Wu is with the Bredesen Center, The University of Tennessee, Knoxville, TN 37996 USA (e-mail:,[email protected]).

Funders	Funder number
SunShot National Laboratory
Battelle
Solar Energy Technologies Office

Keywords

Electronics cooling
genetic algorithms
multichip modules
semiconductor device packaging

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10.1109/TPEL.2018.2881454

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title = "Automated Heatsink Optimization for Air-Cooled Power Semiconductor Modules",

abstract = "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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Automated Heatsink Optimization for Air-Cooled Power Semiconductor Modules

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