Variable switching point predictive torque control with extended prediction horizon

Abstract

This paper introduces the extension of the prediction horizon in the one-step variable switching point predictive torque control (VSP2TC). Even though in the majority of power electronics applications using model predictive control (MPC) based schemes, a prediction horizon of one suffices, the use of longer prediction horizons offers substantial performance benefits. To highlight this, the proposed algorithm is applied to a low voltage (LV) drive system, which comprises a two-level inverter and an induction machine (IM). As it is shown, by extending the prediction horizon, important drive quality indices, such as the torque ripple, and the total harmonic distortion (THD) of the stator currents are reduced. However, the computational effort required for solving the formulated optimization problem in real time can be overwhelming. The implementation of a branch-and-bound technique is introduced to front this tricky matter. Simulation results verify the performance of the presented control strategy.