Performance improvement of induction motor drives with model-based predictive torque control

Abstract

: One of the most important advantages of using modeling and simulation software in design and controlengineering is the ability to predict system behavior within specified conditions. This paper presents a novel errorvector-based control algorithm that aims to reduce torque ripples predicting flux and torque errors in a conventionalvector-controlled induction motor. For this purpose, a new control model has been developed that envisages flux changeby applying probabilistic space vectors’ torque and flux control. In the proposed predictive control algorithm, flux andtorque errors are calculated for each candidate voltage vector. Thus, the optimal output voltage vector that minimizesthe error is determined for the next sampling time. A MATLAB/Simulink model of the proposed control algorithmwas formed and experimental studies were conducted to test the applicability and effectiveness of the proposed methodusing a dSpace 1104 controller board. The results obtained by comparing the effects of the conventional torque controland the proposed predictive direct torque control methods on the motor performance are presented under various speedand loading conditions. The experimental results prove that the proposed algorithm reduced the torque ripples of themotor remarkably when compared to the conventional torque control. The proposed method stands out with its simplestructure due to simplified cost function with the flux model prediction approach and easy applicability with satisfactoryresults.