Towards Data-Driven Strand Transposition Simulation of Multistrand Random Windings

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Abstract

he randomness of the conductor lay in multi-stranded windings used in power-dense electrical machines can cause a wide variation in AC loss across a manufacturing batch. There has been continued focus on the development of strand transposition simulation methods in multistrand random windings to support the estimation of AC loss magnitude and variability. This paper aims to mitigate the limitation faced by such approaches concerning the lack of available verification data by generating a feasible strand transposition dataset. Through characterising the intra- and inter-turn strand mixing present in the simulated strand transpositions, it was observed that the strand mixing distance is Exponentially distributed and that the probability of strand mixing occurring is significantly higher than previously assumed. In order to focus future studies in this area, a simplified strand transposition simulation approach is assessed to highlight the characteristics of strand transpositions that must be represented in future simulation methodologies.
Original languageEnglish
Title of host publication2024 International Conference on Electrical Machines (ICEM)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1-7
Number of pages7
ISBN (Electronic)9798350370607
ISBN (Print)9798350370614
DOIs
Publication statusPublished - 9 Oct 2024
Event 2024 International Conference on Electrical Machines (ICEM) - Italy, Torino
Duration: 1 Sept 20244 Sept 2024

Publication series

Name2024 International Conference on Electrical Machines, ICEM 2024
ISSN (Print)2381-4802
ISSN (Electronic)2473-2087

Conference

Conference 2024 International Conference on Electrical Machines (ICEM)
Abbreviated titleICEM
CityTorino
Period1/09/244/09/24

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

Keywords

  • AC loss
  • strand transposition,
  • random windings

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