{"title":"基于有限元模型的绕线电感器RL参数提取快速随机代理模型的建立","authors":"G. Lossa, O. Deblecker, Z. De Grève, C. Geuzaine","doi":"10.1109/CEFC46938.2020.9451442","DOIUrl":null,"url":null,"abstract":"In this work, fast stochastic surrogate models are derived for extracting RL parameters of wound inductors using the Finite Element method. To this end, the Representative Volume Element (RVE) technique is employed to convert the geometrical uncertainties (e.g. due to conductor positions in the winding window) into material uncertainties (complex permeability and conductivity). The dimensionality of the stochastic input space is in that way reduced, thereby allowing the use of the Polynomial Chaos Expansion (PCE) technique for building the stochastic surrogate.","PeriodicalId":439411,"journal":{"name":"2020 IEEE 19th Biennial Conference on Electromagnetic Field Computation (CEFC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Building Fast Stochastic Surrogate Models for Extracting RL Parameters of Wound Inductors Modeled Using FEM\",\"authors\":\"G. Lossa, O. Deblecker, Z. De Grève, C. Geuzaine\",\"doi\":\"10.1109/CEFC46938.2020.9451442\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work, fast stochastic surrogate models are derived for extracting RL parameters of wound inductors using the Finite Element method. To this end, the Representative Volume Element (RVE) technique is employed to convert the geometrical uncertainties (e.g. due to conductor positions in the winding window) into material uncertainties (complex permeability and conductivity). The dimensionality of the stochastic input space is in that way reduced, thereby allowing the use of the Polynomial Chaos Expansion (PCE) technique for building the stochastic surrogate.\",\"PeriodicalId\":439411,\"journal\":{\"name\":\"2020 IEEE 19th Biennial Conference on Electromagnetic Field Computation (CEFC)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 19th Biennial Conference on Electromagnetic Field Computation (CEFC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CEFC46938.2020.9451442\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 19th Biennial Conference on Electromagnetic Field Computation (CEFC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEFC46938.2020.9451442","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Building Fast Stochastic Surrogate Models for Extracting RL Parameters of Wound Inductors Modeled Using FEM
In this work, fast stochastic surrogate models are derived for extracting RL parameters of wound inductors using the Finite Element method. To this end, the Representative Volume Element (RVE) technique is employed to convert the geometrical uncertainties (e.g. due to conductor positions in the winding window) into material uncertainties (complex permeability and conductivity). The dimensionality of the stochastic input space is in that way reduced, thereby allowing the use of the Polynomial Chaos Expansion (PCE) technique for building the stochastic surrogate.