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Sensorless control of Switched Reluctance Machine

Authors :
Imen Bahri
Eric Berthelot
Demba Diallo
Abdoulaye Sarr
Laboratoire Génie électrique et électronique de Paris (GeePs)
Université Paris-Sud - Paris 11 (UP11)-Université Pierre et Marie Curie - Paris 6 (UPMC)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)
IEEE
Source :
IECON 2016-42nd Annual Conference of the IEEE Industrial Electronics Society, IECON 2016-42nd Annual Conference of the IEEE Industrial Electronics Society, Oct 2016, Florence, Italy. pp.6693-6698, ⟨10.1109/IECON.2016.7793584⟩, IECON
Publication Year :
2016
Publisher :
HAL CCSD, 2016.

Abstract

International audience; The Switched Reluctance Machine is one of the most promising electrical machine in variable speed applications because of its intrinsic robustness and its fault tolerant capability. However, the performances of the machine are deteriorated when a defect affects the position sensor. This paper describes a sensorless control for the switched reluctance machine: two methods based on the characteristics of the machine are proposed to eliminate the requirement of the position sensor. The first one utilizes the phase inductance characteristic to determine the rotor position by injecting a test signal while the phase winding is non-energized. The second one utilizes the flux characteristic to estimate the position by measuring the phase voltage and current. Both methods are evaluated through intensive simulation and the results show their good performance respectively in low speed and high speed region. The flux-based method, implemented in a FPGA, has been evaluated on a test bed. The experimental results confirm the simulation ones with an average position estimation error of around 2° mechanical in the range between 1/3 and the rated speed.

Details

Language :
English
Database :
OpenAIRE
Journal :
IECON 2016-42nd Annual Conference of the IEEE Industrial Electronics Society, IECON 2016-42nd Annual Conference of the IEEE Industrial Electronics Society, Oct 2016, Florence, Italy. pp.6693-6698, ⟨10.1109/IECON.2016.7793584⟩, IECON
Accession number :
edsair.doi.dedup.....60a10b5104fbf4cf4326e0fdcf70b550