Improved sampling algorithm for stochastic modelling of random-wound electrical machines
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Journal Title
Journal ISSN
Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Date
2019-06-17
Major/Subject
Mcode
Degree programme
Language
en
Pages
5
3976-3980
3976-3980
Series
The Journal of Engineering, issue 17
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.Description
| openaire: EC/H2020/339380/EU//ALEM
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
Other note
Citation
Lehikoinen, A, Chiodetto, N, Arkkio, A & Belahcen, A 2019, ' Improved sampling algorithm for stochastic modelling of random-wound electrical machines ', The Journal of Engineering, no. 17, pp. 3976-3980 . https://doi.org/10.1049/joe.2018.8093