A system level comparison of drive topologies for high speed electrical machines

Filippo Savi, Davide Barater, Mauro DI Nardo, Michele Degano, Chris Gerada

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

2 Citations (Scopus)

Abstract

This paper presents a comprehensive comparative study among five different converter topologies all designed to drive a 8.5kW-120krpm surface permanent magnet synchronous machine. The study aims at comparing the considered systems in terms of converter complexity, control complexity and overall efficiency. The assessment of the subsystems' efficiencies is based on a set of decoupled converter-electrical machine simulations. First the designed converters are simulated in Matlab-Simulink environment in order to estimate the converter losses and the current waveforms. Then the latter are used to supply the Finite Elements(FE) model of the electrical machine so to estimate all the loss components present in the real scenario. The results of the carried out study gives a wide understanding of the interaction between the two subsystems and some general design considerations needed to select the converter topology.

Original languageEnglish
Title of host publicationProceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4357-4362
Number of pages6
ISBN (Electronic)9781538611272
DOIs
Publication statusPublished - 15 Dec 2017
Event43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 - Beijing, China
Duration: 29 Oct 20171 Nov 2017

Publication series

NameProceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
Volume2017-January

Conference

Conference43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017
Country/TerritoryChina
CityBeijing
Period29/10/171/11/17

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering
  • Control and Optimization

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