A performance assessment of model predictive direct power control and model predictive direct current control for switched reluctance motor drive systems

Abstract

In this paper, a performance assessment between model predictive direct power control and model predictive direct current control is proposed by using a simplified computational approach for switched reluctance motor drive systems. To reduce the calculation efforts, a reduced set of switching states is employed by combining the space vector modulation strategy with the dead-beat predictive control technique. Specifically, an optimal state of the reduced set of switching states is directly selected and applied in neutral point clamped active front-end rectifiers of switched reluctance motor drive systems. In comparison with the conventional method, the proposed scheme takes into account the 27 candidate switching states to 10. The number of admissible switching states is drastically reduced, which saves the execution time by up to 45% for model predictive direct power control and up to 56% for model predictive direct current control. The unwanted exploration for all available voltage vectors can be eliminated while the flying capacitor voltages are maintained balanced. Meanwhile, the use of the well-known modulation methods can be avoided by the proposed strategy, thus enhancing the dynamic performance. Simulation results obtained with the neutral point clamped active front-end rectifiers confirm the efficacy of two proposed methods.

A Review on Predictive Control Technology for Switched Reluctance Motor System

“…By combining the space vector modulation strategy with the beatless predictive control technique in [105], a reduced set of switching states is employed, which can decrease the computational workload. This control method selects the best state from the reduced switching state group and applies it to the neutral point clamped active front-end rectifier of the switched reluctance motor drive system.…”