Permanent magnet motor design optimisation for sensorless control

Murat Caner, Chris Gerada, Greg Asher

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

This paper looks at a novel optimisation approach to the design of surface mounted permanent magnet (SMPM) machines with self-sensing capabilities. A methodology will be presented which will look at the use of genetic algorithms (GA) to contemporarily maximise the output torque and the self sensing properties of such machines. A GA optimisation environment has been grafted with a finite element analysis (FEA) environment to enable the designer to account for both geometrical and saturation saliencies for an effective determination of the machine's self sensing characteristics. Satisfactory results were obtained in terms of torque maximization and self sensing capability. In addition sensitivity of the major geometrical parameters of the machine will be discussed in terms torque density and the self-sensing.

Original languageEnglish
Title of host publicationInternational Aegean Conference on Electrical Machines and Power Electronics, ACEMP 2011 and Electromotion 2011 Joint Conference
PublisherIEEE Computer Society
Pages670-675
Number of pages6
ISBN (Print)9781467350037
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 International Aegean Conference on Electrical Machines and Power Electronics, ACEMP 2011 and Electromotion 2011 Joint Conference - Istanbul, Turkey
Duration: 8 Sep 201110 Sep 2011

Publication series

NameInternational Aegean Conference on Electrical Machines and Power Electronics, ACEMP 2011 and Electromotion 2011 Joint Conference

Conference

Conference2011 International Aegean Conference on Electrical Machines and Power Electronics, ACEMP 2011 and Electromotion 2011 Joint Conference
Country/TerritoryTurkey
CityIstanbul
Period8/09/1110/09/11

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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