{"title":"Simulation of induction machine starting transients using state variable techniques","authors":"S. Ertem","doi":"10.1109/NAPS.1990.151395","DOIUrl":null,"url":null,"abstract":"A simple, fast, and accurate algorithm for determining induction machine starting transients is presented. The fifth-order system of differential equations is divided into three lower-order subsystems. An iterative solution technique utilizing discrete time linear state-variable techniques is used for solution of two linear subsystems instead of the commonly used inefficient numerical techniques. The solution of the third subsystem is obtained by using well-known numerical techniques. The accuracy of the algorithm is comparable to that of the fifth-order model, and the CPU time requirements are as little as 31% of that required by the fifth-order model.<<ETX>>","PeriodicalId":330083,"journal":{"name":"Proceedings of the Twenty-Second Annual North American Power Symposium","volume":"218 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Twenty-Second Annual North American Power Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAPS.1990.151395","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
A simple, fast, and accurate algorithm for determining induction machine starting transients is presented. The fifth-order system of differential equations is divided into three lower-order subsystems. An iterative solution technique utilizing discrete time linear state-variable techniques is used for solution of two linear subsystems instead of the commonly used inefficient numerical techniques. The solution of the third subsystem is obtained by using well-known numerical techniques. The accuracy of the algorithm is comparable to that of the fifth-order model, and the CPU time requirements are as little as 31% of that required by the fifth-order model.<>