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Full-Speed Sensorless Control Scheme for Permanent Magnet Synchronous Motor Using Artificial Neural Network
  • Al-Kaf, Hasan Ali Gamal ;
  • Mohammed, Sadeq Ali Qasem ;
  • Lee, Kyo Beum
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Publication Year
2023-01-01
Journal
2023 IEEE International Symposium on Sensorless Control for Electrical Drives, SLED 2023
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
2023 IEEE International Symposium on Sensorless Control for Electrical Drives, SLED 2023
Keyword
artificial neural networkExtended back electromotive forcePMSMSensorless methods
Mesh Keyword
Back electromotive forceExtended back electromotive forceFull-speedHigh SpeedLow speedPermanent Magnet Synchronous MotorSensorlessSensorless methodSpeed estimationSpeed sensorless control
All Science Classification Codes (ASJC)
Electrical and Electronic EngineeringMechanical EngineeringComputational Mechanics
Abstract
Extended back electromotive force (EEMF) has been widely used as speed estimation of permanent magnet synchronous motors (PMSMs) due to its excellent performance at medium and high speeds. However, at low speed, EEMF method has low estimation accuracy. Several sensorless methods have combined EEMF with different accurate low-speed estimation techniques to attain a satisfactory estimation performance in the whole speed range. However, the transition between EEMF and low-speed estimation methods is a crucial step that requires two separate speed estimators with different structures. This leads to increased design complexity. Therefore, in this paper, a single sensorless full-speed control is proposed using an artificial neural network (ANN). The proposed ANN method does not require any transition method compared with hybrid full-speed sensorless methods. Simulation results show that proposed ANN can estimate rotor position for full speed compared with EEMF which estimates the rotor speed at medium and high speed.
Language
eng
URI
https://aurora.ajou.ac.kr/handle/2018.oak/36984
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85174573631&origin=inward
DOI
https://doi.org/10.1109/sled57582.2023.10261372
Journal URL
http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=10261339
Type
Conference
Funding
ACKNOWLEDGMENT This work was supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry & Energy (MOTIE) of the Republic of Korea (No. 20206910100160).
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