Analysis and Design of an Electric Machine Employing a Special Stator With Phase Winding Modules and PMs and a Reluctance Rotor

Chandra Sekhar Goli, Murat Gurhan Kesgin, Peng Han, Dan M. Ionel, Somasundaram Essakiappan, James Gafford, Madhav D. Manjrekar

Research output: Contribution to journalArticlepeer-review

Abstract

This paper introduces a new motor design for traction applications that achieves high power density and meets the power density target of 50kW/L target set by the US Department of Energy. The proposed motor has a doubly salient structure with concentrated toroidal 3-phase windings and permanent magnets (PMs) in the stator and a reluctance rotor, improves torque capability and operating speed compared to traditional designs. A design optimization process was conducted to balance efficiency, power density, and power factor. An equivalent circuit in the DQ reference frame is introduced to enable vector control for the proposed special double salient machine. The resulting design was validated through the creation of an open frame lab prototype (OFLP) and an experimental dyno test bench was developed. The prototype was tested through open circuit tests, static torque tests, and unity power factor tests. This paper also discusses the use of synchronous reference frame theory and per-phase diagrams to calculate electric machine parameters. In addition to experimentation, 3D and 2D electromagnetic FEA simulations have been performed for unity power factor operation as a generator to numerically separate the power loss components.

Original languageEnglish
Pages (from-to)9621-9631
Number of pages11
JournalIEEE Access
Volume12
DOIs
StatePublished - 2024

Bibliographical note

Publisher Copyright:
© 2013 IEEE.

Keywords

  • DQ equivalent circuit
  • EV
  • FSPM
  • PMSM
  • Permanent magnet synchronous motor
  • electric vehicles
  • flux switching machine
  • propulsion
  • traction
  • vector control

ASJC Scopus subject areas

  • General Engineering
  • General Computer Science
  • General Materials Science

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