Design and Multiobjective Optimization of a Double-Stator Axial Flux SRM with Full-Pitch Winding Configuration

Fengyuan Yu, Hao Chen, Wenju Yan, Vítor Fernão Pires, João F. A. Martins, Pavol Rafajdus, Antonino Musolino, Luca Sani, Miguel Pablo Aguirre, Muhammad Asghar Saqib, Mohamed Orabi, Xiaodong Li

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)

Abstract

In this article, a novel axial flux double-stator switched reluctance motor (AFDSSRM) is presented and optimized for electric vehicle applications. AFDSSRM adopts the axial arrangement of double-stator and inner rotor structure with a full-pitch winding configuration. The flux generated by the two stators cancels each other at the unaligned position, and then, a low unaligned inductance barely affected by saturation is achieved, which is the primary advantage of the AFDSSRM. First, the topology and power equation of the motor are presented briefly. Due to a large number of dimensional parameters of the proposed structure, comprehensive sensitivity analysis is used to classify the design parameters into strong- and weak-sensitive classes, and a multilayer optimization approach is adopted for the variables of both classes. The response surface method combined with the multiobjective genetic algorithm is employed to optimize the strong-sensitive variables, while the Taguchi algorithm is applied to optimize the weak-sensitive variables. Moreover, the 3-D finite element model is established to analyze the electromagnetic characteristics of the motor. Finally, a prototype motor is manufactured, and the experimental results verify the effectiveness of the proposed structure and the optimization method.

Original languageEnglish
Pages (from-to)4348-4364
Number of pages17
JournalIEEE Transactions on Transportation Electrification
Volume8
Issue number4
DOIs
Publication statusPublished - Dec 2022

Keywords

  • Axial flux switched reluctance machines (SRMs)
  • electromagnetic performance
  • finite-element analysis
  • full-pitch winding
  • multiobjective optimization

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