Improved sampling algorithm for stochastic modelling of random-wound electrical machines

Antti Lehikoinen*, Nicola Chiodetto, Antero Arkkio, Anouar Belahcen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Random-wound electrical machines often suffer from high circulating current losses. These losses vary from machine to machine in a stochastic fashion. This study proposes an improved sampling algorithm for quantifying the uncertainty inherent in random windings. The algorithm is then combined with a circuit model to perform Monte Carlo analysis on the losses. The results are compared to measurements, and a good agreement is observed.

Original languageEnglish
Pages (from-to)3976-3980
Number of pages5
Journal The Journal of Engineering
Issue number17
DOIs
Publication statusPublished - 17 Jun 2019
MoE publication typeA1 Journal article-refereed

Keywords

  • stochastic processes
  • electric machines
  • Monte Carlo methods
  • machine windings
  • sampling methods
  • improved sampling algorithm
  • stochastic modelling
  • random-wound electrical machines
  • high circulating current losses
  • circuit model
  • Monte Carlo analysis

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