Shlimet, S.B. orcid.org/0009-0001-2084-6180 and Griffo, A. orcid.org/0000-0001-5642-2921 (2025) PWM-based speed and position estimations for permanent magnet synchronous machines. Applied Sciences, 15 (18). 9859. ISSN: 2076-3417
Abstract
A PWM-based rotor position and speed estimator is presented in this study. The method is based on the measurement of the current response to conventional space vector pulse width-modulated voltage (SV-PWM) for PMSM drive applications. Model reference adaptive system (MRAS) estimators are often used for sensorless speed estimation. A MRAS typically uses two models: the reference model (voltage model) and the adaptive model (current model). The voltage model in flux-based MRAS uses the integration of stator voltages to calculate the stator flux. The pure integrator is usually replaced by a low-pass filter; however, this results in phase errors at low frequencies. The position is estimated using oversampling and averaging over a switching SV-PWM cycle, eliminating the need for integrators. Extensive experimental tests are presented to evaluate the performance of the PWM-based estimator. The results of the experiments demonstrate good performance at various speeds and under various load circumstances, in both motoring and regenerating modes. The proposed method also shows robustness to changes in motor parameters.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2025 The Authors. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Keywords: | model reference adaptive system (MRAS); PMSM; sensorless; SV-PWM; speed estimation |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > School of Electrical and Electronic Engineering |
Date Deposited: | 14 Oct 2025 10:24 |
Last Modified: | 14 Oct 2025 10:24 |
Published Version: | https://doi.org/10.3390/app15189859 |
Status: | Published |
Publisher: | MDPI AG |
Refereed: | Yes |
Identification Number: | 10.3390/app15189859 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:232881 |