System-Level Robust Design Optimization of a Permanent Magnet Motor Under Design Parameter Uncertainties

Jaegyeong Mun, K. K. Choi, Dong Hun Kim

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

1 Scopus citations

Abstract

In the presence of design parameter uncertainties, a system-level robust design optimization (RDO) method for a permanent magnet motor is proposed to enhance steady and dynamic performances of the whole motor drive system. To achieve the goal, the influence of individual motor parameters on transient system responses is investigated essentially. Then material characteristic of each motor component due to the operating temperature fluctuation is examined as well. Finally, a conventionally customized motor drive system is fully simulated based on the finite element method, and the motor is optimized by the univariate dimension reduction method (uDRM).

Original languageEnglish
Title of host publicationCEFC 2022 - 20th Biennial IEEE Conference on Electromagnetic Field Computation, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665468336
DOIs
StatePublished - 2022
Event20th Biennial IEEE Conference on Electromagnetic Field Computation, CEFC 2022 - Virtual, Online, United States
Duration: 24 Oct 202226 Oct 2022

Publication series

NameCEFC 2022 - 20th Biennial IEEE Conference on Electromagnetic Field Computation, Proceedings

Conference

Conference20th Biennial IEEE Conference on Electromagnetic Field Computation, CEFC 2022
Country/TerritoryUnited States
CityVirtual, Online
Period24/10/2226/10/22

Keywords

  • electromagnetics
  • optimization
  • reliability theory
  • robustness

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