{"title":"Efficiency optimization of a vector controlled induction motor drive using an artificial neural network","authors":"E. S. Abdin, G.A. Ghoneem, H. Diab, S. A. Deraz","doi":"10.1109/IECON.2003.1280646","DOIUrl":null,"url":null,"abstract":"This paper presents an approach for efficiency optimization of a vector controlled induction motor drive. The optimum flux-producing current is obtained using an artificial neural network. The artificial neural network model is established using Matlab/Simulink and based on the load torque and speed data of an indirect vector-controlled induction motor drive. The change of iron core loss resistance due to flux and frequency variation is taken into consideration. Simulation results of the proposed approach show a significant improvement in energy saving and efficiency optimization.","PeriodicalId":403239,"journal":{"name":"IECON'03. 29th Annual Conference of the IEEE Industrial Electronics Society (IEEE Cat. No.03CH37468)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"44","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IECON'03. 29th Annual Conference of the IEEE Industrial Electronics Society (IEEE Cat. No.03CH37468)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IECON.2003.1280646","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 44
Abstract
This paper presents an approach for efficiency optimization of a vector controlled induction motor drive. The optimum flux-producing current is obtained using an artificial neural network. The artificial neural network model is established using Matlab/Simulink and based on the load torque and speed data of an indirect vector-controlled induction motor drive. The change of iron core loss resistance due to flux and frequency variation is taken into consideration. Simulation results of the proposed approach show a significant improvement in energy saving and efficiency optimization.