Optimized sizing of IPM machines for automotive traction application

Giorgio Valente, David Gerada, Michele Degano, Christopher Gerada, John Foulsham, Daniel Beeby

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

3 Citations (Scopus)

Abstract

This paper presents the implementation of an electrical machine design tool including its overall architecture. The tool is flexible and can be employed for the sizing of any permanent magnet synchronous machine. The case study considered in this work is the design of V-shaped interior permanent magnet synchronous machine for automotive applications. The preliminary design stage is considered with the aim of selecting the optimum machine pole pairs number and rotation speed. A multi-objective genetic algorithm is linked to the design tool and adopted to maximize the machine power density in terms of kW/L as well as to minimize the machine cost. The outcomes of this work are showing the variation of the above objective functions with respect to the pole-pair number and gearbox ratio as well as their effect on the machine efficiency.

Original languageEnglish
Title of host publication2019 IEEE International Electric Machines and Drives Conference, IEMDC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages970-975
Number of pages6
ISBN (Electronic)9781538693490
DOIs
Publication statusPublished - May 2019
Externally publishedYes
Event11th IEEE International Electric Machines and Drives Conference, IEMDC 2019 - San Diego, United States
Duration: 12 May 201915 May 2019

Publication series

Name2019 IEEE International Electric Machines and Drives Conference, IEMDC 2019

Conference

Conference11th IEEE International Electric Machines and Drives Conference, IEMDC 2019
Country/TerritoryUnited States
CitySan Diego
Period12/05/1915/05/19

Keywords

  • Automotive
  • Genetic algorithm
  • High speed electrical machines
  • Optimization design
  • Permanent magnet synchronous machine

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Mechanical Engineering

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