CQICO and multi-objective thermal optimization for high speed PM generator

Xiaochen Zhang, Weili Li, Chris Gerada, He Zhang, Jing Li, Michael Galea, David Gerada, Junci Cao

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

1 Citation (Scopus)

Abstract

This paper proposes a novel Continuous Quantum Immune Clonal Optimization (CQICO) algorithm for thermal optimization on an 117kW high speed permanent magnet generator (HSPMG). Via mixing the Quantum Computation into the Immune Cloning Algorithm, the new algorithm is benefited with better population diversity, higher global searching ability, and faster convergence which approved by simulation results. Then, the improved algorithm is applied to seek an optimized slot groove can improve HSPMG thermal performance, in which the 3-D fluid-thermal coupling analyses are processed with a multi-objective optimal group composed of the highest temperature and the temperature difference. Both the proposed algorithm and the obtained conclusions are of significances in the design and optimization of the cooling system in electric machines.

Original languageEnglish
Title of host publicationIEEE CEFC 2016 - 17th Biennial Conference on Electromagnetic Field Computation
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509010325
DOIs
Publication statusPublished - 12 Jan 2017
Externally publishedYes
Event17th Biennial IEEE Conference on Electromagnetic Field Computation, IEEE CEFC 2016 - Miami, United States
Duration: 13 Nov 201616 Nov 2016

Publication series

NameIEEE CEFC 2016 - 17th Biennial Conference on Electromagnetic Field Computation

Conference

Conference17th Biennial IEEE Conference on Electromagnetic Field Computation, IEEE CEFC 2016
Country/TerritoryUnited States
CityMiami
Period13/11/1616/11/16

Keywords

  • CQICO
  • Fluid-thermal
  • Groove
  • HSPMG
  • Optimization

ASJC Scopus subject areas

  • Computational Mathematics
  • Instrumentation
  • Electrical and Electronic Engineering

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