Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12188/25541
DC Field | Value | Language |
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dc.contributor.author | Cvetkovski, Goga | en_US |
dc.contributor.author | Petkovska, Lidija | en_US |
dc.date.accessioned | 2023-01-25T11:16:25Z | - |
dc.date.available | 2023-01-25T11:16:25Z | - |
dc.date.issued | 2021-04-25 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.12188/25541 | - |
dc.description.abstract | The permanent magnet brushless DC motors and permanent magnet synchronous motors have been widely used in industrial high performance applications in recent years. Although they have good electrical, magnetic and performance characteristics there is one parameter named cogging torque that has a negative influence on the performance characteristics of the motor. This pulsating torque is produced due to the interaction between the stator teeth and the permanent magnets. The minimization of the torque ripple in those permanent magnet motors is of great importance and is generally achieved by a special motor design which in the design process involves a variation of many geometrical motor parameters. In this paper a novel approach is introduced where different nature inspired algorithms, such as genetic algorithm and cuckoo search algorithm are used as a torque minimization tool, where the function definition of the maximum value of the cogging torque is used as an objective function. For that purpose, a proper mathematical presentation of the maximum value of the cogging torque for the analyzed synchronous motor is developed and used. For the purpose of the different motor models analysis, the initial motor and the optimized motor models are modelled and analyzed using a finite element method approach. The cogging torque is analytically and numerically calculated and the results for all the models are presented. | en_US |
dc.language.iso | en | en_US |
dc.publisher | IEEE | en_US |
dc.subject | permanent magnet synchronous motor, optimization methods, cogging torque, genetic algorithm, particle swarm, cuckoo search, finite element method | en_US |
dc.title | Cogging Torque Minimisation of PM Synchronous Motor Using Nature Based Algorithms | en_US |
dc.type | Proceeding article | en_US |
dc.relation.conference | 2021 IEEE 19th International Power Electronics and Motion Control Conference (PEMC), Gliwice, Poland, 2021. | en_US |
dc.identifier.doi | 10.1109/pemc48073.2021.9432507 | - |
dc.identifier.url | http://xplorestaging.ieee.org/ielx7/9432488/9432490/09432507.pdf?arnumber=9432507 | - |
dc.identifier.fpage | 1 | - |
dc.identifier.lpage | 6 | - |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
Appears in Collections: | Faculty of Electrical Engineering and Information Technologies: Conference Papers |
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