Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/10110
Title: Genetic Algorithm Applied in Optimal Design of PM Disc Motor Using Specific Power as Objective, in the book - Studies in Computational Intelligence - Computational Methods for the Innovative Design of Electrical Devices,
Authors: Cvetkovski Goga, Petkovska Lidija, Gair Sinclair
Keywords: Genetic Algorithm, Optimal Design, Linear Scaling, Magnetic Field, Distribution, Genetic Algorithm Apply
Issue Date: 2010
Publisher: Springer, Berlin, Heidelberg
Source: Cvetkovski G., Petkovska L., Gair S. (2010) Genetic Algorithm Applied in Optimal Design of PM Disc Motor Using Specific Power as Objective. In: Wiak S., Napieralska-Juszczak E. (eds) Computational Methods for the Innovative Design of Electrical Devices. Studies in Computational Intelligence, vol 327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16225-1_13
Abstract: In general the optimal design of electrical machines is a constrained maximization/minimization problem with a big number of optimization parameters and variety of constraints. This makes it a difficult problem to solve for the deterministic methods, but on the other hand quite an easy task for the stochastic methods, especially for the Genetic Algorithms (GAs). When optimizing an electric motor, there are multiple choices of the objective function available. The objective function is the specific property of the machine to be optimized, for example efficiency, torque, volume or cost. The application of the permanent magnet disc motor (PMDM) is in electric vehicle and therefore there are several objectives that should be tackled in the design procedure, such as an increased efficiency, reduced total weight of the motor or increased power/weight ratio (specific power). In this work an optimal design of a PMDM using specific power as objective function is performed. In the design procedure performed on the PM disc motor, genetic algorithm, as an optimization tool is used. Comparative analysis of the optimal motor solution and its parameters in relation to the initial model is presented.
URI: http://hdl.handle.net/20.500.12188/10110
DOI: https://doi.org/10.1007/978-3-642-16225-1_13
Appears in Collections:Faculty of Electrical Engineering and Information Technologies: Book Chapters

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