Open AccessComparative study and performance evaluation of analytical methods for surface mounted permanent magnet brushless motors
Author(s) -
Dwivedi Ankita,
Singh Santosh Kumar,
Srivastava Rakesh K.,
Mahendra Som N.
Publication year - 2016
Publication title -
iet power electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.637
H-Index - 77
eISSN - 1755-4543
pISSN - 1755-4535
DOI - 10.1049/iet-pel.2016.0179
Subject(s) - magnet , magnetic field , magnetic flux , flux (metallurgy) , fourier analysis , fourier transform , fourier series , surface (topology) , field (mathematics) , computer science , mechanical engineering , control theory (sociology) , engineering , physics , materials science , mathematics , mathematical analysis , artificial intelligence , control (management) , quantum mechanics , geometry , pure mathematics , metallurgy
Analysis and determination of magnetic field distribution of surface mounted permanent magnet (SMPM) motors has always been a topic of research. Though a number of methods like two‐dimensional numerical and analytical methods have been proposed to evaluate the magnetic field and parameters of radial flux SMPM motors, the methods developed for axial flux permanent magnet motors are mainly three dimensional. Numerical methods provide accurate results but are not suitable for initial design analysis. The analytical methods are known for their accuracy, convenience, as well as are less time consuming than numerical methods. The analytical methods like conventional design method, magnetic equivalent circuit, generalised machine theory and Fourier analysis present in the literature for SMPM motor have been investigated in this study and the results obtained are compared and evaluated for radial flux SMPM and axial flux SMPM. Experimental results are included to demonstrate the percentage error obtained from different methods and denote the accuracy. From the comparison of different results, it can be concluded that the Fourier transform method is more realistic approach and is capable of computing the performance as well as field distribution simultaneously.