Electrical Machine Loss Distribution and Thermal Parameter Identification through Experimentally Informed Virtual Prototyping

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

1 Citation (Scopus)
49 Downloads (Pure)

Abstract

Precise loss predictions inform key decisions in the design of high performance electrical machines. Detailed understanding and effective management of operational losses are critical to maximising power density and operational life. Imprecise loss predictions can stem from lack of accurate material and interface data. A method is presented to identify key thermal parameters and AC loss distributions, without construction of a full scale prototype. Using a 3D Virtual Prototype of a machine subassembly, calibrated by experimental data, key parameters such as the conductor-slot thermal conductivity are extracted and implications on machine thermal performance and build quality are inferred.
Original languageEnglish
Title of host publication2019 IEEE Energy Conversion Congress and Exposition (ECCE)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages4853-4859
Number of pages7
ISBN (Electronic)978-1-7281-0395-2
DOIs
Publication statusPublished - 28 Nov 2019
EventECCE 2019: IEEE Energy Conversion Congress & Expo. - Baltimore, United States
Duration: 29 Sep 2019 → …

Publication series

NameEnergy Conversion Congress and Exposition, ECCE, IEEE
PublisherIEEE
ISSN (Electronic)2329-3748

Conference

ConferenceECCE 2019
Abbreviated titleECCE 2019
CountryUnited States
CityBaltimore
Period29/09/19 → …

Keywords

  • PM electrical machine
  • thermal analysis
  • machine sub-assembly
  • model calibration
  • virtual prototype

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  • Cite this

    North, D. J., Collins, S. M., Simpson, N., & Mellor, P. (2019). Electrical Machine Loss Distribution and Thermal Parameter Identification through Experimentally Informed Virtual Prototyping. In 2019 IEEE Energy Conversion Congress and Exposition (ECCE) (pp. 4853-4859). (Energy Conversion Congress and Exposition, ECCE, IEEE). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ECCE.2019.8912683