Design Optimization of a Short-Term Duty Electrical Machine for Extreme Environment

Puvan Arumugam, Emmanuel Amankwah, Adam Walker, Chris Gerada

Research output: Journal PublicationArticlepeer-review

6 Citations (Scopus)

Abstract

This paper presents design optimization of a short-term duty electrical machine for extreme environments of high temperature and high altitudes. For such extreme environmental conditions of above 80 °C and altitudes of 30 km, thermal loading limits are a critical consideration in machines, especially if high power density and high efficiency are to be achieved. The influence of different material on the performance of such machines is investigated. Also, the effect of different slot and pole combinations are studied for machines used for such extreme operating conditions but with short duty. In the research, a nondominated sorting genetic algorithm (NSGAII) considering an analytical electromagnetic model, structural and thermal model together with finite element methods are used to optimize the design of the machine for such environments achieving high efficiencies and high power density with relatively minimal computational time. The adopted thermal model is then validated through experiments and then implemented within the genetic algorithm. It is shown that, generally, the designs are thermally limited where the pole numbers are limited by volt-amps drawn from the converter. The design consisting of a high slot number allows for improving the current loading and thus, significant weight reduction can be achieved.

Original languageEnglish
Article number7938395
Pages (from-to)9784-9794
Number of pages11
JournalIEEE Transactions on Industrial Electronics
Volume64
Issue number12
DOIs
Publication statusPublished - Dec 2017
Externally publishedYes

Keywords

  • Extreme environment
  • genetic algorithm (GA)
  • optimization
  • short duty
  • thermal management

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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