{"title":"3D FEM Model of a Hybrid Stepper Using Scalar-Vector Potential Formulations","authors":"O. Craiu, T. Ichim, Liviu Cristian Popescu","doi":"10.1109/ATEE58038.2023.10108283","DOIUrl":null,"url":null,"abstract":"The paper presents an analysis of a few 3D Finite Element Method (FEM) models based on different magnetic scalar and vector potential combinations, of a bi-phase hybrid stepper motor (HSM). The computing time is compared against a reference solution determined using only the magnetic vector potential. The model accuracy is estimated by comparing the HSM holding torque characteristics computed for each model. As HSM 3D FEM models generate matrix systems of equations with millions of unknowns, reducing the computational time and computer memory requirement are essential, hence the practical relevance of this study.","PeriodicalId":398894,"journal":{"name":"2023 13th International Symposium on Advanced Topics in Electrical Engineering (ATEE)","volume":"150 5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 13th International Symposium on Advanced Topics in Electrical Engineering (ATEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ATEE58038.2023.10108283","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
The paper presents an analysis of a few 3D Finite Element Method (FEM) models based on different magnetic scalar and vector potential combinations, of a bi-phase hybrid stepper motor (HSM). The computing time is compared against a reference solution determined using only the magnetic vector potential. The model accuracy is estimated by comparing the HSM holding torque characteristics computed for each model. As HSM 3D FEM models generate matrix systems of equations with millions of unknowns, reducing the computational time and computer memory requirement are essential, hence the practical relevance of this study.