Accurate torque control of position sensorless switched reluctance drives

Aachen / ISEA (2018, 2019) [Book, Dissertation / PhD Thesis]

Page(s): 1 Online-Ressource (x, 154 Seiten) : Illustrationen, Diagramme


Switched reluctance drives (SRDs) are getting more attractive due to the progress in the field of power electronics in the last decades due to their simple mechanical structure and reliability, as well as their potential for low-cost mass production. Well-known disadvantages of SRDs, such as acoustic noise and torque pulsation, can be handled by means of advanced control strategies. However, sophisticated torque control algorithms require the exact rotor position, which is usually detected by costly absolute position sensors. This thesis investigates position detection algorithms that extract the necessary rotor position from the measured terminal quantities, namely phase voltages and currents including the current gradient. Here, computation devices such as fast DSPs and FPGAs are employed, due to their oversampling capability and computational power. The detection algorithms are universal and can be applied with state-of-the-art torque controllers, such as direct instantaneous torque control, current profiling methods and conventional current control. First, the position estimation at low speed including standstill is discussed. In the frame of this work, the well-known signal injection method is improved by appropriate signal conditioning and early position detection, so that the injected currents can be kept at low levels. The algorithm is able to detect and supress the very prominent effect of phase coupling in switched reluctance machines. In the second part, the application of the flux-linkage method at medium and high speeds is investigated. To improve its accuracy, the method is enhanced by adopting a series of measures including an online adaptation of the temperature dependent stator resistance and an adaptive band-pass filter.



Ralev, Iliya Valentinov


de Doncker, Rik W.
Kennel, Ralph


  • REPORT NUMBER: RWTH-2019-03071