An Improved Model Predictive Direct Torque Control for Induction Machine Drives

摘要

The conventional model predictive direct torque control (MPDTC) method uses all of the voltage vectors available from a two level voltage source inverter for the prediction of the stator flux and stator current, which leads to a heavy computational burden. This paper proposes an improved model predictive direct torque control method. The stator flux predictive controller is obtained from an analysis of the relationship between the stator flux and the torque, which can be used to calculate the desired voltage vector based on the stator flux and torque reference. Then this method only needs to evaluate three voltage vectors in the sector of the desired voltage vector. As a result, the computational burden of the conventional MPDTC is effectively reduced. The time delay introduced by the computational time causes the stator current to oscillate around its reference. It also increases the current and torque ripples. To address this problem, a delay compensation method is adopted in this paper. Furthermore, the switching frequency of the inverter is significantly reduced by introducing the constraint of the power semiconductor switching number to the cost function of the MPDTC. Both simulation and experimental results are presented to verify the validity and feasibility of the proposed method.