Surrogate Model-Based Heat Sink Design for Energy Storage Converters

Gege Qiao, Wenping Cao (), Yawei Hu, Jiucheng Li, Lu Sun and Cungang Hu
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Gege Qiao: School of Electrical Engineering and Automation, Anhui University, Hefei 230031, China
Wenping Cao: School of Electrical Engineering and Automation, Anhui University, Hefei 230031, China
Yawei Hu: School of Electrical Engineering and Automation, Anhui University, Hefei 230031, China
Jiucheng Li: Asunx Semiconductors Co., Ltd., Hefei 230093, China
Lu Sun: Asunx Semiconductors Co., Ltd., Hefei 230093, China
Cungang Hu: School of Electrical Engineering and Automation, Anhui University, Hefei 230031, China

Energies, 2023, vol. 16, issue 3, 1-13

Abstract: As forced-air cooling for heat sinks is widely used in the cooling design of electrical and electronic equipment, their thermal performance is of critical importance for maintaining excellent cooling capacity while reducing the size and weight of the heat sink and the equipment as a whole. This paper presents a method based on the combination of computational fluid dynamics (CFD) simulation and surrogate models to optimize heat sinks for high-end energy storage converters. The design takes the thermal resistance and mass of the heat sink as the optimization goals and looks for the best design for the fin height, thickness and spacing, as well as the base thickness. The analytical and numerical results show that the thermal resistance and mass of the heat sink are reduced by the proposed algorithms, as are the temperatures of the heating elements. Test results verify the effectiveness of the optimization method combining CFD simulation with surrogate models.

Keywords: computational fluid dynamics (CFD); energy storage; surrogate model; design optimization; heat sinks; power converters (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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