{"title":"基于粒子群算法的轮式永磁电机优化设计","authors":"Lassaad Zaaraoui, A. Mansouri, H. Trabelsi","doi":"10.1109/IINTEC.2017.8325937","DOIUrl":null,"url":null,"abstract":"The present work deals with the optimal design of the geometrical parameters of an in-wheel permanent magnet motor with an exterior rotor and concentrated windings. In order to achieve this end, three-particle swarm optimization (PSO) based algorithms were applied: Multi-Objective Particle Swarm Optimizer (OMOPSO), Speed-constrained Multi-Objective PSO (SMPSO) and Dual Multi-Objective PSO (DMOPSO). Firstly, the machine design is transformed to a multi-objective constrained optimization problem. Ten design variables were selected to be optimized and two objective functions were used: the machine mass minimization and its efficiency maximization. Secondly, the three PSO-based techniques were applied and the optimization results are presented and discussed.","PeriodicalId":348452,"journal":{"name":"International Conferences on Internet of Things, Embedded Systems and Communications","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"PSO-based optimal design of in-wheel permanent magnet motor\",\"authors\":\"Lassaad Zaaraoui, A. Mansouri, H. Trabelsi\",\"doi\":\"10.1109/IINTEC.2017.8325937\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The present work deals with the optimal design of the geometrical parameters of an in-wheel permanent magnet motor with an exterior rotor and concentrated windings. In order to achieve this end, three-particle swarm optimization (PSO) based algorithms were applied: Multi-Objective Particle Swarm Optimizer (OMOPSO), Speed-constrained Multi-Objective PSO (SMPSO) and Dual Multi-Objective PSO (DMOPSO). Firstly, the machine design is transformed to a multi-objective constrained optimization problem. Ten design variables were selected to be optimized and two objective functions were used: the machine mass minimization and its efficiency maximization. Secondly, the three PSO-based techniques were applied and the optimization results are presented and discussed.\",\"PeriodicalId\":348452,\"journal\":{\"name\":\"International Conferences on Internet of Things, Embedded Systems and Communications\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conferences on Internet of Things, Embedded Systems and Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IINTEC.2017.8325937\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conferences on Internet of Things, Embedded Systems and Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IINTEC.2017.8325937","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PSO-based optimal design of in-wheel permanent magnet motor
The present work deals with the optimal design of the geometrical parameters of an in-wheel permanent magnet motor with an exterior rotor and concentrated windings. In order to achieve this end, three-particle swarm optimization (PSO) based algorithms were applied: Multi-Objective Particle Swarm Optimizer (OMOPSO), Speed-constrained Multi-Objective PSO (SMPSO) and Dual Multi-Objective PSO (DMOPSO). Firstly, the machine design is transformed to a multi-objective constrained optimization problem. Ten design variables were selected to be optimized and two objective functions were used: the machine mass minimization and its efficiency maximization. Secondly, the three PSO-based techniques were applied and the optimization results are presented and discussed.