Integrated motor drive design for weight optimization

Benjamin Cheong, Paolo Giangrande, Michael Galea, Pericle Zanchetta, Patrick Wheeler

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

5 Citations (Scopus)

Abstract

The More-Electric Aircraft (MEA) concept has been introduced as part of the process of reducing the environmental impact of air travel. Incorporating more electrical systems including motor drives has become increasingly attractive researched. High power density across the complete system is a key factor in the realization of this technology. This paper considers a motor drive sizing procedure with a focus on optimizing the main weight contributors which are identified as the electrical machine, grid input filters and converter cooling system. A multi-level integrated optimization method is then proposed, followed by an example of its application incorporating the sizing procedure above. Comparison of results between single-level optimizations and multi-level optimizations are then presented. Finally, this paper presents the software validation of the sizing functions performed using different multi-physics software.

Original languageEnglish
Title of host publication2017 IEEE Energy Conversion Congress and Exposition, ECCE 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages816-823
Number of pages8
ISBN (Electronic)9781509029983
DOIs
Publication statusPublished - 3 Nov 2017
Externally publishedYes
Event9th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2017 - Cincinnati, United States
Duration: 1 Oct 20175 Oct 2017

Publication series

Name2017 IEEE Energy Conversion Congress and Exposition, ECCE 2017
Volume2017-January

Conference

Conference9th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2017
Country/TerritoryUnited States
CityCincinnati
Period1/10/175/10/17

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Renewable Energy, Sustainability and the Environment
  • Control and Optimization

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