Open AccessPermanent Magnet Synchronous Motor Design using Grey Wolf Optimizer Algorithm
Author(s) -
Yannis L. Karnavas,
Ioannis D. Chasiotis,
Emmanouil L Peponakis
Publication year - 2016
Publication title -
international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 22
ISSN - 2088-8708
DOI - 10.11591/ijece.v6i3.pp1353-1362
Subject(s) - rotor (electric) , computer science , pulley , torque , magnet , maximization , synchronous motor , context (archaeology) , control theory (sociology) , minification , permanent magnet synchronous motor , automotive engineering , control engineering , engineering , mathematical optimization , mechanical engineering , mathematics , electrical engineering , physics , paleontology , control (management) , artificial intelligence , biology , thermodynamics , programming language
Common high-torque low-speed motor drive schemes combine an induction motor coupled to the load by a mechanical subsystem which consists of gears, belt/pulleys or camshafts. Consequently, these setups present an inherent drawback regarding to maintenance needs, high costs and overall system deficiency. Thus, the replacement of such a conventional drive with a properly designed low speed permanent magnet synchronous motor (PMSM) directly coupled to the load, provides an attractive alternative. In this context, the paper deals with the design evaluation of a 5kW/50rpm radial flux PMSM with surface-mounted permanent magnets and inner rotor topology. Since the main goal is the minimization of the machine's total losses and therefore the maximization of its efficiency, the design is conducted by solving an optimization problem. For this purpose, the application of a new meta-heuristic optimization method called “ Grey Wolf Optimizer ” is studied. The effectiveness of the method in finding appropriate PMSM designs is then evaluated. The obtained results of the applied method reveal satisfactorily enhanced design solutions and performance when compared with those of other optimization techniques.