T. Sivakumar, S. Sankarakumar, T. Mahalakshmi, P. Hemalaxmi
{"title":"基于进化算法的三相鼠笼式异步电动机设计优化","authors":"T. Sivakumar, S. Sankarakumar, T. Mahalakshmi, P. Hemalaxmi","doi":"10.1109/ICRAECC43874.2019.8995153","DOIUrl":null,"url":null,"abstract":"The mathematical design of motor consist of nonlinear expressions, several constraints such as core saturation, thermal limits, etc., makes the manual design of motor more complex and obtaining better design is not possible with conventional design methods. To overcome this difficulty evolution algorithm based computer simulations can be used to get better performance motors. This paper discusses the application of Gravitational Search Algorithm (GSA) and Real- Coded Genetic algorithm (RGA) for optimal design of three- phase squirrel cage induction motor. The motor design is optimized using efficiency and material cost as the fitness function. The optimally designed induction machine is compared with the design developed using modified differential evolution based induction motor design and found GSA based motor design provides a better design with maximum efficiency and minimum losses. Computer simulations were carried out using MATLAB 2017a.","PeriodicalId":137313,"journal":{"name":"2019 International Conference on Recent Advances in Energy-efficient Computing and Communication (ICRAECC)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Design Optimization of Three Phase Squirrel Cage Induction Motor Using Evolutionary Algorithm\",\"authors\":\"T. Sivakumar, S. Sankarakumar, T. Mahalakshmi, P. Hemalaxmi\",\"doi\":\"10.1109/ICRAECC43874.2019.8995153\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The mathematical design of motor consist of nonlinear expressions, several constraints such as core saturation, thermal limits, etc., makes the manual design of motor more complex and obtaining better design is not possible with conventional design methods. To overcome this difficulty evolution algorithm based computer simulations can be used to get better performance motors. This paper discusses the application of Gravitational Search Algorithm (GSA) and Real- Coded Genetic algorithm (RGA) for optimal design of three- phase squirrel cage induction motor. The motor design is optimized using efficiency and material cost as the fitness function. The optimally designed induction machine is compared with the design developed using modified differential evolution based induction motor design and found GSA based motor design provides a better design with maximum efficiency and minimum losses. Computer simulations were carried out using MATLAB 2017a.\",\"PeriodicalId\":137313,\"journal\":{\"name\":\"2019 International Conference on Recent Advances in Energy-efficient Computing and Communication (ICRAECC)\",\"volume\":\"123 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Recent Advances in Energy-efficient Computing and Communication (ICRAECC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRAECC43874.2019.8995153\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Recent Advances in Energy-efficient Computing and Communication (ICRAECC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRAECC43874.2019.8995153","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design Optimization of Three Phase Squirrel Cage Induction Motor Using Evolutionary Algorithm
The mathematical design of motor consist of nonlinear expressions, several constraints such as core saturation, thermal limits, etc., makes the manual design of motor more complex and obtaining better design is not possible with conventional design methods. To overcome this difficulty evolution algorithm based computer simulations can be used to get better performance motors. This paper discusses the application of Gravitational Search Algorithm (GSA) and Real- Coded Genetic algorithm (RGA) for optimal design of three- phase squirrel cage induction motor. The motor design is optimized using efficiency and material cost as the fitness function. The optimally designed induction machine is compared with the design developed using modified differential evolution based induction motor design and found GSA based motor design provides a better design with maximum efficiency and minimum losses. Computer simulations were carried out using MATLAB 2017a.