{"title":"Topology Optimization with Improved Genetic Algorithm of an Electromagnetic Actuator","authors":"S. Ruzbehi, I. Hahn","doi":"10.1109/COMPUMAG45669.2019.9032829","DOIUrl":null,"url":null,"abstract":"In conventional optimization, geometric optimization with changing the boundaries of the geometric shape is common, but in this study, topological optimization is applied to give the designer more freedom to achieve a machine design, which fulfils the customer’s goals. Topological optimization is common in the field of mechanical engineering, but in the design of electrical machines and electromagnetic actuators there is still an open space for its application.Having an electrical machine with high torque and low weight is one of the desired goals, which is investigated in this study. The implementation of the proposed method is applied to an electromagnetic actuator in order to optimize its topology or structure. To assess the validity of the proposed method, while considering the goals, the design of a simple magnetic actuator using a metaheuristic optimization method is presented as a global search. To overcome the generation of intermediate material characteristics in the cells of the design area, a binary genetic algorithm (GA) is used. Also, to enhance the low convergence rate of the GA, several chromosomes for each subarea of the design space are used independently of each other and operate at the same time, therefore, lead to a significant reduction of the computational time. The actuator’s force is calculated to gain the best material distribution in the discretized design area. After the automatic optimization process some manual changes in the material distribution are made to improve the manufacturability. The given design goals have been successfully achieved using the proposed topological optimization method.","PeriodicalId":317315,"journal":{"name":"2019 22nd International Conference on the Computation of Electromagnetic Fields (COMPUMAG)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 22nd International Conference on the Computation of Electromagnetic Fields (COMPUMAG)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMPUMAG45669.2019.9032829","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In conventional optimization, geometric optimization with changing the boundaries of the geometric shape is common, but in this study, topological optimization is applied to give the designer more freedom to achieve a machine design, which fulfils the customer’s goals. Topological optimization is common in the field of mechanical engineering, but in the design of electrical machines and electromagnetic actuators there is still an open space for its application.Having an electrical machine with high torque and low weight is one of the desired goals, which is investigated in this study. The implementation of the proposed method is applied to an electromagnetic actuator in order to optimize its topology or structure. To assess the validity of the proposed method, while considering the goals, the design of a simple magnetic actuator using a metaheuristic optimization method is presented as a global search. To overcome the generation of intermediate material characteristics in the cells of the design area, a binary genetic algorithm (GA) is used. Also, to enhance the low convergence rate of the GA, several chromosomes for each subarea of the design space are used independently of each other and operate at the same time, therefore, lead to a significant reduction of the computational time. The actuator’s force is calculated to gain the best material distribution in the discretized design area. After the automatic optimization process some manual changes in the material distribution are made to improve the manufacturability. The given design goals have been successfully achieved using the proposed topological optimization method.