Multidomain Optimization of High-Power-Density PM Electrical Machines for System Architecture Selection

Dmitry Golovanov, Luca Papini, David Gerada, Zeyuan Xu, Chris Gerada

Research output: Journal PublicationArticlepeer-review

41 Citations (Scopus)

Abstract

The power density of electrical machines for transport applications has become a critical aspect and target of optimization. This paper looks at the development of an intelligent, rapid, flexible, and multidomain tool to aid for system-level optimization of electrical machines within next-generation high power density applications. The electromagnetic, thermal, and mechanical aspects are wholly integrated, thus enabling the optimization including the nonactive mass. The implementation and overall architecture of the tool are described, and using a case study drawn from the aerospace industry, the tool is used to compare the power density of various surface permanent magnet topologies including single airgap and dual airgap machines, highlighting the particular suitability of the dual rotor topology in achieving the best power to mass ratio. Finally, the accuracy of the tool is highlighted by practical realization and experimental validation.

Original languageEnglish
Pages (from-to)5302-5312
Number of pages11
JournalIEEE Transactions on Industrial Electronics
Volume65
Issue number7
DOIs
Publication statusPublished - Jul 2018
Externally publishedYes

Keywords

  • High power density
  • multidomain
  • optimization
  • permanent magnet machines
  • transportation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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