Low Complexity Model Predictive Flux Control for Three-Level Neutral-Point Clamped Inverter-Fed Induction Motor Drives Without Weighting Factor

Abstract

Tuning of weighting factors is a very complex task in the implementation of conventional finite set predictive torque control (FS-PTC) for three-level neutral-point-clamped (3L-NPC) inverter fed IM drive. The choice of these weighting factors strongly influences the control objectives such as flux, torque, and neutral point voltage (NPV). Moreover, the computational burden is high as all 27 switching states are enumerated for the evaluation of a cost function involving multiple objectives. To reduce the complexity of the conventional FS-PTC, this article proposes a high-efficient single-vector-based predictive flux control for an IM drive fed by a 3L-NPC inverter. The proposed cascaded predictive flux and NPV control evaluates 13 vectors for outer predictive flux control and two switching states for the inner predictive NPV control. It significantly reduces the computational load as the number of enumerations is reduced by more than 50%. The nontrivial process of weighting factor calculation is no longer required. The complexity reduction and the elimination of weighting factors are achieved without sacrificing the transient and steady-state performances in terms of torque and stator flux responses, total harmonic distortion of stator currents, NPV variation, and average switching frequency, compared to the conventional method as verified by experimental results.