Heat Sink Design for WBG Power Modules Based on Fourier Series and Evolutionary Multi-Objective Multi-Physics Optimization

Abstract

Optimal heat dissipation in power modules can significantly increase their power density. Removing the generated heat is critical for capturing the benefits of advanced semiconductor materials and improving the reliability of the device operation. This study proposes a design optimization method for liquid-cooled heat sinks that use a Fourier analysis-based tool and an evolutionary optimization algorithm to optimize the heat sink geometry for specified objectives. The optimized heat sink geometry was compared with state-of-the-art solutions in the literature based on finite element analysis of different designs. The proposed methodology can develop complex geometries that outperform conventional heat sink geometries. Optimized heat sink design from the proposed method was fabricated and tested in an experimental setup under representative operating conditions. The experimental setup was also modeled in the finite element model that was used for the proposed heat sink optimization method. The experimental results show that developed finite element models can predict the thermal and flow performance of the complex design with high fidelity, and the results validate the proposed design approach.

Over-Current Capability of Silicon Carbide and Silicon Devices for Short Power Pulses with Copper and Phase Change Materials below the Chip

“…One point to note is that the heat sinks can be selected in various ways depending on the application and power density [62,63]. Due to high current density for SiC MOSFETs, the heat sink is designed in such a way that the average temperature of the MOSFETs for the nominal current values is limited to approximately 100 • C. However, in order to make a fair comparison between Si and SiC devices, the same thermal design is chosen for the Si power module.…”

Exploring the Potential of Mixed Fourier Series in Signal Processing Applications Using One-Dimensional Smooth Closed-Form Functions with Compact Support: A Comprehensive Tutorial

“…First, ringing artifacts are removed because we can control the type of convergence; for example: Corollary 5 (Convergence Everywhere). If g ∈ C 1 [0, T] and P 1 {g; t} are given by (8) with coefficients ( 31)- (33), then the Fourier series of r(t) = g(t) − P 1 {g; t}, ∀t ∈ [0, T] has uniform convergence.…”

“…On the one hand, harmonic analysis allows the study of the original function or phenomenon through the superposition of simpler trigonometric functions. This analysis represents a wide branch of study in mathematics [1][2][3] and is used in many applications in physics [4][5][6], engineering [7][8][9], medicine [10][11][12], and music [13]. Fourier synthesis, on the other hand, uses a linear combination of basis functions to approximate the original function [14], which has many applications in boundary value problems [15][16][17], data interpolation [18][19][20][21], and compression [22].…”