NDLI: Optimal design of geometrical and physical parameters of permanent magnet machines in the purpose to reduce its vibratory behavior

Content Provider	IEEE Xplore Digital Library
Author	Ferkha, N. Mekideche, M.R. Miraoui, A. Djerdir, A. N-Diaye, A.O. Peyraut, F.
Copyright Year	2013
Description	Author affiliation: Lab. Syst. et Transp. SET, Univ. de Technol. de Belfort-Montbeliard UTBM, Belfort, France (Miraoui, A.; Djerdir, A.; N-Diaye, A.O.) \|\| Lab. M3M, Univ. de Technol. de Belfort-Montbeliard, Belfort, France (Peyraut, F.) \|\| Lab. LAMEL, Univ. de Jijel, Ouled Aissa, Algeria (Ferkha, N.; Mekideche, M.R.)
Abstract	Permanent magnet synchronous machines (PMSM) have high efficiency and torque density, and have already been employed in hybrid electric vehicles. However, one of their disadvantages is the inherent cogging torque, which is a kind of torque ripple and it would be better to minimize. This torque, sometimes, can be an important source of noise and vibrations. In this paper, the effect of the geometric characteristics of the stator on the vibratory behavior of electrical machines is illustrated. The optimum geometry for obtaining a minimum vibration level has been reached. For this purpose, an approach by using the Artificial Intelligent (AI) and the Finite Element Method (FEM) is proposed to solve the magneto-mechanical problem of geometrical parameters identification in the optimization process. The obtained results by Genetic Algorithm (GA) method have been presented.
Starting Page	1
Ending Page	6
File Size	2521205
Page Count	6
File Format	PDF
e-ISBN	9781479906888
DOI	10.1109/EPECS.2013.6713063
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-10-02
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Geometry Finite element method Torque Genetic algorithm Magneto-mechanical coupling Permanent magnet synchronous machines Neural network Vibration reduction Equations Optimization Optimal design
Content Type	Text
Resource Type	Article

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