Parameters identification of 11-phase Torus generator using Particle Swarm Optimization technique

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Axial-flux, Permanent-magnet machines are used in different applications where the power and torque density requirements are very high. These machines have simple structures, relatively high efficiencies and low cost. The parameters of these machines are very small compared with the parameters of conventional machines. Different measuring methods are normally used in order to obtain good estimates of the machine parameters. These methods are difficult to perform, costly and time consuming. This paper proposes the use of Particle Swarm Optimization (PSO) technique to predict the self and mutual inductances of the 11-phase Torus machine automatically.

Original languageEnglish
Title of host publicationIEEE Power and Energy Society 2008 General Meeting: Conversion and Delivery of Electrical Energy in the 21st Century, PES
DOIs
Publication statusPublished - 2008
EventIEEE Power and Energy Society 2008 General Meeting: Conversion and Delivery of Electrical Energy in the 21st Century, PES - Pittsburgh, PA, United States
Duration: Jul 20 2008Jul 24 2008

Other

OtherIEEE Power and Energy Society 2008 General Meeting: Conversion and Delivery of Electrical Energy in the 21st Century, PES
CountryUnited States
CityPittsburgh, PA
Period7/20/087/24/08

Keywords

  • Parameter identification
  • Particle Swarm Optimization technique
  • Torus machine

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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    Al-Hinai, A., & Al-Badi, A. (2008). Parameters identification of 11-phase Torus generator using Particle Swarm Optimization technique. In IEEE Power and Energy Society 2008 General Meeting: Conversion and Delivery of Electrical Energy in the 21st Century, PES [4596691] https://doi.org/10.1109/PES.2008.4596691