[en] In this work, fast stochastic surrogate models are derived for extracting RL parameters of wound inductors using the Finite Element method. To this end, the Representative Volume Element (RVE) technique is employed to convert the geometrical uncertainties (e.g. due to conductor positions in the winding window) into material uncertainties (complex permeability and conductivity). The dimensionality of the stochastic input space is in that way reduced, thereby allowing the use of the Polynomial Chaos Expansion (PCE) technique for building the stochastic surrogate.
Disciplines :
Electrical & electronics engineering
Author, co-author :
Lossa, Geoffrey; General Physics Unit, University of Mons, Faculty of Engineering, Belgium
Deblecker, Olivier; Power Electrical Engineering Unit, UMons, Faculty of Engineering
De Grève, Zacharie; Power Electrical Engineering Unit, UMons, Faculty of Engineering
Geuzaine, Christophe ; Université de Liège - ULiège > Montefiore Institute of Electrical Engineering and Computer Science
Language :
English
Title :
Building Fast Stochastic Surrogate Models for Extracting RL Parameters of Wound Inductors Modeled Using FEM
Publication date :
16 November 2020
Event name :
2020 IEEE 19th Biennial Conference on Electromagnetic Field Computation (CEFC)
Event place :
Virtual, Pisa, Ita
Event date :
16-11-2020 => 18-11-2020
Audience :
International
Main work title :
CEFC 2020 - Selected Papers from the 19th Biennial IEEE Conference on Electromagnetic Field Computation
Publisher :
Institute of Electrical and Electronics Engineers Inc.
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