Low speed estimation of DTC controlled induction motor drive using MRAS

Abstract

Direct Torque controlled (DTC) induction motor drive gives direct control of stator flux and electromagnetic torque. Conventional speed sensors are replaced in sensor less DTC to improve the reliability, noise immunity and to reduce the complexity of the system. In sensor less DTC the rotor speed estimation at low speeds is degraded by the stator resistance parameter variations due to temperature, dead time effects and voltage drop in power electronics devices. The open loop speed estimation used in sensor less DTC depends on various machine parameters. The stator resistance variation at low speeds degrades the speed estimation. In this paper investigation of sensor less DTC controlled induction motor at low speed range is carried out and to improve the speed estimation at low speed closed loop Model Reference Adaptive Scheme (MRAS) is used for speed estimation. Simulation is carried out in Matlab/ Simulink platform and results are compared and presented.

Low Speed Estimation of Sensorless DTC Induction Motor Drive Using MRAS with Neuro Fuzzy Adaptive Controller

“…The torque error and flux error obtained are tuned by the corresponding PI controllers to generate the reference voltage vector required for the SVM to select the required stator voltage vector to exactly compensate the flux and torque error. SVM reduces the torque ripple and switching frequency is maintained constant [17], [18].…”