Niklas König, E. Grasso, K. Schuhmacher, M. Nienhaus
{"title":"Parameter identification of star-connected PMSMs by means of a sensorless technique","authors":"Niklas König, E. Grasso, K. Schuhmacher, M. Nienhaus","doi":"10.1109/EVER.2018.8362359","DOIUrl":null,"url":null,"abstract":"An important tool in the field of Permanent Magnet Synchronous Motors (PMSMs) is parameter identification, which allows for final stage inspection, adaptive control and condition monitoring. Common identification approaches require the PMSM to be mounted into a test-bench with encoders, which is complicated or not possible for some machines. In order to address this issue, this work combines a Recursive Least-Squares based parameter identification algorithm with the sensorless control technique Direct Flux Observer (DFO). The developed identification technique is implemented on a microcontroller and experimental results on different kind of PMSMs are shown and discussed.","PeriodicalId":344175,"journal":{"name":"2018 Thirteenth International Conference on Ecological Vehicles and Renewable Energies (EVER)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Thirteenth International Conference on Ecological Vehicles and Renewable Energies (EVER)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EVER.2018.8362359","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
An important tool in the field of Permanent Magnet Synchronous Motors (PMSMs) is parameter identification, which allows for final stage inspection, adaptive control and condition monitoring. Common identification approaches require the PMSM to be mounted into a test-bench with encoders, which is complicated or not possible for some machines. In order to address this issue, this work combines a Recursive Least-Squares based parameter identification algorithm with the sensorless control technique Direct Flux Observer (DFO). The developed identification technique is implemented on a microcontroller and experimental results on different kind of PMSMs are shown and discussed.