Optimized voltage vector selection for dual-star induction motor: Robust predictive direct torque control-based hysteresis-free approach

The dual-star induction machine is a widely adopted multiphase machine in industrial applications, thanks to its superior reliability in managing power supply faults and enhanced robustness. This study presents a robust predictive DTC strategy for a dual-star induction motor supplied by dual-voltage source inverters. Relying on a cost function optimization, the suggested predictive DTC algorithm replaces traditional hysteresis regulators and switching tables typically employed in classical DTC, determining the optimal sequence of voltage space vectors. Regarding speed regulation, the proposed MPC framework incorporates integral action, eliminating steady-state inaccuracies and improving disturbance rejection under model uncertainties and external perturbations. Real-time validation on the OPAL-RT platform confirms the effectiveness of the proposed scheme. Compared with conventional DTC, torque and flux ripples are reduced by 83.95 % and 74.75 %, respectively, while current THD decreases by 77.89 %. In addition, the speed response time improves by 82.5 %, and the rejection time by 97 %. These results highlight the robustness and efficiency of the proposed RPDTC technique, making it a strong candidate for high-performance DSIM drive applications.