Design and Analysis of a Novel Axial Flux Permanent Magnet Assisted Synchronous Reluctance Motor       
Yazarlar (2)
Dr. Öğr. Üyesi Emrah ESER Tokat Gaziosmanpaşa Üniversitesi, Türkiye
Nurettin Üstkoyuncu
Erciyes Üniversitesi, Türkiye
Makale Türü Özgün Makale
Makale Alt Türü SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale
Dergi Adı Journal of Electrical Engineering and Technology
Dergi ISSN 1975-0102 Wos Dergi Scopus Dergi
Dergi Tarandığı Indeksler SCI-Expanded
Dergi Grubu Q3
Makale Dili İngilizce
Basım Tarihi 01-2025
Cilt No 20
Sayı 3
Sayfalar 1429 / 1438
DOI Numarası 10.1007/s42835-024-02052-x
Makale Linki https://doi.org/10.1007/s42835-024-02052-x
Özet
Synchronous reluctance motors (SynRMs) have become very popular in recent years due to their low cost and high efficiency advantages. However, the low power factor is one of the biggest disadvantages. Axial-flux (AF) motors are particularly characterised by their volume/power ratio, which is one of the most important factors in the design of a motor. In this study, the design and analysis of an axial-flux permanent magnet assisted synchronous reluctance motor (AF-PMa-SynRM) has been taken into account and a prototype motor has been realized for experimental studies. The inner and outer diameters of the rotor of the prototype motor are designed to be larger than the stator in order to assess the leakage fluxes at the return ends of the stator windings. The barrier arms of the rotor have been designed as angled. The novelty of this study is that the design and manufacture of the AF-PMa-SynRM with mentioned features has been realised for the first time in the literature to the best of our knowledge. Torque fluctuation, which is one of the problems of SynRM and it has been improved by optimising the rotor barriers, especially the barrier arms in the study. Finite Element Analysis (FEA) and experimental results have been compared with each other.
Anahtar Kelimeler
Axial-flux permenant magnet assisted synchronous reluctance motor (AF-PMa-SynRM) | Finite element analysis (FEA) | Multi-objective genetic algorithm (MOGA) | Synchronous reluctance motor (SynRM)