Multi-objective optimisation of the HSPMM rotor based on the multi-physics surrogate model

Rui Dai, Yue Zhang, Tianyu Wang, Fengge Zhang, Chris Gerada, Yuan Zhang

Research output: Journal PublicationArticlepeer-review

Abstract

High-speed permanent magnetic machine (HSPMM) is attracting more attention due to its high power density, compact size, small rotating inertia, and rapid response capability. However, the design of the HSPMM rotor is a non-linear, multi-physics coupled process that makes it difficult to build an accurate mathematical model for optimisation. This study proposes a multi-objective optimisation method based on the multi-physics surrogate model (MPSM). This method uses an MPSM to replace the finite element model (FEM) for optimisation, which can effectively solve the problem of non-convergence and time consumption of the traditional FEM in the optimisation process. Finally, a 1.1 MW, 18,000 r/min HSPMM is produced and related experiments are carried out; the feasibility of the method proposed in this study for HSPMM optimisation is verified.

Original languageEnglish
Pages (from-to)1616-1629
Number of pages14
JournalIET Electric Power Applications
Volume15
Issue number12
DOIs
Publication statusPublished - Dec 2021
Externally publishedYes

Keywords

  • AC machines
  • AC motors
  • finite element analysis
  • optimisation
  • permanent magnet machines
  • permanent magnet motors
  • rotors

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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