A. Tessarolo, F. Luise, M. Mezzarobba, M. Bortolozzi, L. Branz
{"title":"Special magnetic wedge design optimization with genetic algorithms for cogging torque reduction in permanent-magnet synchronous machines","authors":"A. Tessarolo, F. Luise, M. Mezzarobba, M. Bortolozzi, L. Branz","doi":"10.1109/ESARS.2012.6387431","DOIUrl":null,"url":null,"abstract":"Permanent magnet synchronous machines, especially if designed with open stator slots, may suffer from important cogging torque issues. A special magnetic wedge design has been presented in a companion paper to cope with this problem. The design of such wedge is herein processed through a genetic algorithm in order to find the optimal configuration, which leads to cogging torque minimization. An optimal design configuration is found and compared to non-optimal ones to quantify the benefits that can be achieved by genetic optimization.","PeriodicalId":243822,"journal":{"name":"2012 Electrical Systems for Aircraft, Railway and Ship Propulsion","volume":"120 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Electrical Systems for Aircraft, Railway and Ship Propulsion","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ESARS.2012.6387431","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Permanent magnet synchronous machines, especially if designed with open stator slots, may suffer from important cogging torque issues. A special magnetic wedge design has been presented in a companion paper to cope with this problem. The design of such wedge is herein processed through a genetic algorithm in order to find the optimal configuration, which leads to cogging torque minimization. An optimal design configuration is found and compared to non-optimal ones to quantify the benefits that can be achieved by genetic optimization.