Fast simulation of transient temperature distributions in power modules using multi-parameter model reduction

In this study, a three-dimensional model with multi-parameter order reduction is applied to the thermal modelling of power electronics modules with complex geometries. Finite element or finite difference method can be used to establish accurate mathematical models for thermal analyses. Unfortunately, the resulting computational complexity hinders the analysis in parametric studies. This study proposes a parametric order reduction technique that can significantly increase simulation efficiency without significant penalty in the prediction accuracy. The method, based on the block Arnoldi method, is illustrated with reference to a multi-chip SiC power module mounted on a forced air-cooled finned heat sink with a variable mass flow rate

Parameterized Model Order Reduction

This Chapter introduces parameterized, or parametric, Model Order Reduction (pMOR). The Sections are offered in a prefered order for reading, but can be read independently. Section 5.1, written by Jorge Fernández Villena, L. Miguel Silveira, Wil H.A. Schilders, Gabriela Ciuprina, Daniel Ioan and Sebastian Kula, overviews the basic principles for pMOR. Due to higher integration and increasing frequency-based effects, large, full Electromagnetic Models (EM) are needed for accurate prediction of the real behavior of integrated passives and interconnects. Furthermore, these structures are subject to parametric effects due to small variations of the geometric and physical properties of the inherent materials and manufacturing process. Accuracy requirements lead to huge models, which are expensive to simulate and this cost is increased when parameters and their effects are taken into account. This Section introduces the framework of pMOR, which aims at generating reduced models for systems depending on a set of parameters