Francesco Puglisi, Saverio Giulio Barbieri, Sara Mantovani, Giampaolo Devito, Stefano Nuzzo
{"title":"用于牵引应用的永磁辅助同步磁阻机的多物理场和多目标优化设计","authors":"Francesco Puglisi, Saverio Giulio Barbieri, Sara Mantovani, Giampaolo Devito, Stefano Nuzzo","doi":"10.1177/09544062241240888","DOIUrl":null,"url":null,"abstract":"This contribution addresses the rotor design process of a Permanent Magnet-assisted Synchronous Reluctance Machine by adopting a multi-physics and multi-objective optimization algorithm. A Finite Element (FE) approach is employed to determine the electromagnetic and structural responses during the optimization. In particular, a detailed FE structural modeling is used, which often is based on simplifications and inaccuracies in the available literature. A genetic algorithm is adopted, with the objectives being the maximization of the mean torque, the minimization of the torque ripple and the minimization of the stress in the rotor. A parametric analysis of the geometric features precedes the optimization to establish the design variables which mostly affect the machine performance, and thus to reduce the computational cost of the optimization. The presented methodology consists of a useful tool for the final stages of the design process, and provides a rotor with a torque ripple reduced by 15.1% compared to an existing design used as a benchmark, while the mean torque and the maximum stress remain the same as the original configuration.","PeriodicalId":20558,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-physics and multi-objective optimization of a permanent magnet-assisted synchronous reluctance machine for traction applications\",\"authors\":\"Francesco Puglisi, Saverio Giulio Barbieri, Sara Mantovani, Giampaolo Devito, Stefano Nuzzo\",\"doi\":\"10.1177/09544062241240888\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This contribution addresses the rotor design process of a Permanent Magnet-assisted Synchronous Reluctance Machine by adopting a multi-physics and multi-objective optimization algorithm. A Finite Element (FE) approach is employed to determine the electromagnetic and structural responses during the optimization. In particular, a detailed FE structural modeling is used, which often is based on simplifications and inaccuracies in the available literature. A genetic algorithm is adopted, with the objectives being the maximization of the mean torque, the minimization of the torque ripple and the minimization of the stress in the rotor. A parametric analysis of the geometric features precedes the optimization to establish the design variables which mostly affect the machine performance, and thus to reduce the computational cost of the optimization. The presented methodology consists of a useful tool for the final stages of the design process, and provides a rotor with a torque ripple reduced by 15.1% compared to an existing design used as a benchmark, while the mean torque and the maximum stress remain the same as the original configuration.\",\"PeriodicalId\":20558,\"journal\":{\"name\":\"Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2024-03-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1177/09544062241240888\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1177/09544062241240888","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
Multi-physics and multi-objective optimization of a permanent magnet-assisted synchronous reluctance machine for traction applications
This contribution addresses the rotor design process of a Permanent Magnet-assisted Synchronous Reluctance Machine by adopting a multi-physics and multi-objective optimization algorithm. A Finite Element (FE) approach is employed to determine the electromagnetic and structural responses during the optimization. In particular, a detailed FE structural modeling is used, which often is based on simplifications and inaccuracies in the available literature. A genetic algorithm is adopted, with the objectives being the maximization of the mean torque, the minimization of the torque ripple and the minimization of the stress in the rotor. A parametric analysis of the geometric features precedes the optimization to establish the design variables which mostly affect the machine performance, and thus to reduce the computational cost of the optimization. The presented methodology consists of a useful tool for the final stages of the design process, and provides a rotor with a torque ripple reduced by 15.1% compared to an existing design used as a benchmark, while the mean torque and the maximum stress remain the same as the original configuration.
期刊介绍:
The Journal of Mechanical Engineering Science advances the understanding of both the fundamentals of engineering science and its application to the solution of challenges and problems in engineering.