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Sensorless direct torque control of PMSM with reduced model extended Kalman filter

Citace: GLASBERGER, T., MUŽÍKOVÁ, V., PEROUTKA, Z., ŠMÍDL, V. Sensorless direct torque control of PMSM with reduced model extended Kalman filter. In Proceedings of IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society. New York: IEEE, 2013. s. 8239-8244. ISBN: 978-1-4799-0224-8 , ISSN: 1553-572X
Druh: STAŤ VE SBORNÍKU
Jazyk publikace: eng
Anglický název: Sensorless direct torque control of PMSM with reduced model extended Kalman filter
Rok vydání: 2013
Místo konání: New York
Název zdroje: IEEE
Autoři: Ing. Tomáš Glasberger Ph.D. , Ing. Vendula Mužíková , Prof. Ing. Zdeněk Peroutka Ph.D. , Doc. Ing. Václav Šmídl Ph.D.
Abstrakt EN: The aim of this paper is to study the use of the Extended Kalman filer (EKF) for sensorless control of a permanent magnet synchronous motor (PMSM) drive controlled by direct torque control (DTC). In contrast to the vector control, the DTC allows for better compensation of the dead-time effects, however, it also needs to run with much shorter sampling period. The challenge for the EKF is to minimize its execution time. This is achieved by using state space model of the drive with only two state variables, the rotor speed and the rotor position, which will be known as the reduced model. We show in simulations and experiments, that the EKF with this reduced model has the same performance as the four-dimensional full order model at much lower computational cost. This allows to use the EKF even in DTC with very short sampling time and take full advantage of the dead-time compensation. Due to better reconstruction of the voltage vector, the sensorless DTC is able to operate the drive at lower speed than the vector control with the same estimator. All experiments were carried out on a laboratory prototype of the drive with rated power of 11 kW and 44 poles. Control algorithms using DTC with sampling periods of 30 or 50 \mu s and vector control with sampling period of 125 \mu s were compared. The sensorless DTC with the reduced model EKF was found to be equal to DTC with the full model EKF in terms of performace and superior in terms of computational cost. Both sensorless DTC algorithms outperformed the vector control algorithm in accuracy of the estimation especially at low speed.
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