Parameter Determination and Drive Control Analysis of Axial Flux Permanent Magnet Synchronous Motors

Authors

  • Attila Nyitrai
    Affiliation

    Multidisciplinary Doctoral School of Engineering Sciences, Széchenyi István Univeryity, H-9026 Győr, Egyetem tér 1., Hungary

  • Gergely Szabó
    Affiliation

    Department of Electric Power Engineering, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, H-1111 Budapest, Egry József street 18., Hungary

  • Sándor R. Horváth
    Affiliation

    Department of Electric Power Engineering, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, H-1111 Budapest, Egry József street 18., Hungary

https://doi.org/10.3311/PPee.19714

Abstract

Axial flux electric motors have received a lot of attention in recent years due to successful implementations in industrial or traction applications. Particularly, axial flux permanent magnet synchronous motors (AFPMSM) can be an attractive choice in case of high torque-density requirements or when the drive environment (packaging) is geometrically limited to a disc-shaped motor. However, compared to radial flux motors, axial flux machine modeling possibilities are much less documented. In the present study, different electromagnetic modeling approaches have been compared through an example AFPMSM design. The motor parameters were determined by analytical and finite element methods. A 2D equivalent model (2D Linear Motor Modeling Approach – 2D-LMMA) and a 3D model results have been compared. The calculated values were used to carry out a drive control analysis of the axial flux motor.

Keywords:

axial flux motor; motor parameters; drive control simulation; electromagnetic analysis; finite element analysis

Published Online

2022-05-17

How to Cite

Nyitrai, A., Szabó, G., Horváth, S. R. “Parameter Determination and Drive Control Analysis of Axial Flux Permanent Magnet Synchronous Motors”, Periodica Polytechnica Electrical Engineering and Computer Science, 66(2), pp. 205–214, 2022. https://doi.org/10.3311/PPee.19714

Issue

Section

Articles