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Title: | Impact of Solder Voids on IGBT Thermal Behavior: A Multi-Methodological Approach | Authors: | ALAVI, Omid DE CEUNINCK, Ward DAENEN, Michael |
Issue Date: | 2024 | Publisher: | MDPI | Source: | Electronics (Basel), 13 (11) (Art N° 2188) | Abstract: | This study investigates the thermal behavior of Insulated Gate Bipolar Transistors (IGBTs) with a focus on the influence of solder voids within the device. Utilizing a combination of Finite Element Method (FEM) simulations, X-ray imaging, and SEM-EDX analysis, we accurately modeled the internal structure of IGBTs to assess the impact of void characteristics on thermal resistance. The findings reveal that the presence and characteristics of solder voids-particularly their size, number, and distribution-significantly affect the thermal resistance of IGBT devices. Experimental measurements validate the FEM model's accuracy, confirming that voids disrupt the heat flow path, which can lead to increased thermal resistance and potential device failure. Five regression models, including Gaussian process regression (GPR) and neural networks, were employed to predict the thermal resistance based on void characteristics, with the GPR models demonstrating superior performance. The optimal GPR RQ model consistently provided accurate predictions with an RMSE of 0.0050 and R2 of 0.9728. Using the void percentage as the only input parameter for the regression models significantly impacted the prediction accuracy, showing the importance of the void extraction method. This study shows the necessity of minimizing solder voids and offers a robust methodological framework for a better prediction of the reliability of IGBTs. | Notes: | Alavi, O (corresponding author), Hasselt Univ, IMO IMOMEC, Wetenschapspk 1, B-3590 Diepenbeek, Belgium.; Alavi, O (corresponding author), IMEC, Kapeldreef 75, B-3001 Heverlee, Belgium.; Alavi, O (corresponding author), EnergyVille, Thor Pk 8310, B-3600 Genk, Belgium. omid.alavi@uhasselt.be; ward.deceuninck@uhasselt.be; michael.daenen@uhasselt.be |
Keywords: | finite element method (FEM);Gaussian process regression (GPR);insulated gate bipolar transistors (IGBTs);machine learning;power electronics reliability;solder voids | Document URI: | http://hdl.handle.net/1942/43350 | e-ISSN: | 2079-9292 | DOI: | 10.3390/electronics13112188 | ISI #: | 001246836600001 | Rights: | 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). | Category: | A1 | Type: | Journal Contribution |
Appears in Collections: | Research publications |
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