Print Email Facebook Twitter Genetic Algorithm–Assisted Design of Redistribution Layer Vias for a Fan-Out Panel-Level SiC MOSFET Power Module Packaging Title Genetic Algorithm–Assisted Design of Redistribution Layer Vias for a Fan-Out Panel-Level SiC MOSFET Power Module Packaging Author Fan, Jiajie (Fudan University; Research Institute of Fudan University, Ningbo) Qian, Yichen (Hohai University) Chen, Wei (Fudan University) Jiang, Jing (Fudan University) Tang, Zhuorui (Fudan University) Fan, Xuejun (Lamar University) Zhang, Kouchi (TU Delft Electronic Components, Technology and Materials) Contributor O'Conner, L. (editor) Date 2022 Abstract A fan-out panel-level packaging (FOPLP) with an embedded redistribution layer (RDL) via interconnection reduces the size, thermal resistance, and parasitic inductance of power module packaging. In this study, the effect of the RDL via size on the reliability of a FOPLP SiC MOSFET power module was investigated. To improve the thermal management and thermal cycling reliability of the designed SiC module, genetic algorithm (GA)–assisted optimization methods were proposed to optimize the RDL via size. First, the heat dissipation and the plastic work density of the SiC MOSFET module with various via diameters and depths were simulated using finite element simulations. Next, both the ant colony optimization-backpropagation neural network (ACOBPNN) with finite element simulation and the nondominated sorting genetic algorithm (NSGA-II) with theoretical model were developed to optimize the RDL via size. The results revealed that: (1) smaller via depth and size reduce the heat dissipation and thermal cycling reliability of the RDL via; (2) through both the ACO-BPNN and NSGA-II, the same optimal heat dissipation and plastic work density can be achieved in the designed module. (3) ACO-BPNN with assist of finite element simulation can provide a more effective optimization in complex packaging structure. Subject SiC MOSFETFOPLPACO-BPNNNSGA-IIReliability optimization To reference this document use: http://resolver.tudelft.nl/uuid:e66f228f-2c08-4ff3-a548-8ff91806d262 DOI https://doi.org/10.1109/ECTC51906.2022.00049 Publisher IEEE, Piscataway Embargo date 2023-07-01 ISBN 978-1-6654-7944-8 Source Proceedings of the 2022 IEEE 72nd Electronic Components and Technology Conference (ECTC) Event 2022 IEEE 72nd Electronic Components and Technology Conference (ECTC), 2022-05-31 → 2022-06-03, San Diego, United States Bibliographical note Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. Part of collection Institutional Repository Document type conference paper Rights © 2022 Jiajie Fan, Yichen Qian, Wei Chen, Jing Jiang, Zhuorui Tang, Xuejun Fan, Kouchi Zhang Files PDF Genetic_AlgorithmAssisted ... kaging.pdf 1.14 MB Close viewer /islandora/object/uuid:e66f228f-2c08-4ff3-a548-8ff91806d262/datastream/OBJ/view