An Improved Feature-Position-Based Sensorless Direct Torque Control Scheme for SRM Drives at Medium-High Speeds

This paper proposes a novel sensorless direct torque control (DTC) method based on the inductance inflection point to improve the torque performance and enhance the reliability of the switched reluctance motor. The conventional sensorless methods suffer the required prior knowledge, modelling complexity, and computational burden. A straightforward sensorless approach utilizing feature position is developed to identify the phase commutation point and implement DTC for torque ripple mitigation. Furthermore, the impact of the saturation effect is considered for accurate position detection and torque estimation. The proposed sensorless DTC method is verified by simulation in MATLAB/Simulink.

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Publication Details

Published
2024-11-26
DOI
https://doi.org/10.1109/esars-itec60450.2024.10819924
Primary Topic
Iterative Learning Control Systems
Type
article
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article

An Improved Feature-Position-Based Sensorless Direct Torque Control Scheme for SRM Drives at Medium-High Speeds

Chongyang Tian, Babak Nahid‐Mobarakeh
Iterative Learning Control Systems
article

An Improved Feature-Position-Based Sensorless Direct Torque Control Scheme for SRM Drives at Medium-High Speeds

Chongyang Tian, Babak Nahid‐Mobarakeh
article en

Abstract

This paper proposes a novel sensorless direct torque control (DTC) method based on the inductance inflection point to improve the torque performance and enhance the reliability of the switched reluctance motor. The conventional sensorless methods suffer the required prior knowledge, modelling complexity, and computational burden. A straightforward sensorless approach utilizing feature position is developed to identify the phase commutation point and implement DTC for torque ripple mitigation. Furthermore, the impact of the saturation effect is considered for accurate position detection and torque estimation. The proposed sensorless DTC method is verified by simulation in MATLAB/Simulink.

McMaster University (CA)
Affordable and clean energy
Openalex Percentile: Top 70%
Iterative Learning Control Systems
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