Analysis of Parameter Variability in an Integrated Wireless Power Transfer System via Partial Least-Squares Regression

Mourad Larbi, Riccardo Trinchero, Flavio G. Canavero, Philippe Besnier, Madhavan Swaminathan

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

This article deals with the application of the partial least-squares (PLS) regression to the uncertainty quantification of an integrated wireless power transfer with 30 random variables. It considers the development of surrogate models using a limited set of training samples in order to estimate statistical quantities of the converter efficiency with a relatively low computational cost compared with the standard brute-force Monte Carlo (MC) simulation. The strength, the performance, and the features of the proposed modeling approach are then compared with the ones of an advanced probabilistic surrogate model combining the least-squares support vector machine (LS-SVM) and the Gaussian process regression (GPR). The MC simulation is considered as a reference.

Original languageEnglish (US)
Article number9116816
Pages (from-to)1795-1802
Number of pages8
JournalIEEE Transactions on Components, Packaging and Manufacturing Technology
Volume10
Issue number11
DOIs
StatePublished - Nov 2020

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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