Investigation of predictive direct torque control of Double Star permanent magnet synchronous machine (DSPMSM)

Abstract

In order to enhance the performance of Direct Torque Control (DTC) applied to a double-star permanent magnet synchronous machine (DSPMSM) in termes to reduce the ripples of torque and current, in this work we propose a Predictive DTC Control for DSPMSM. The primary objective of this control approach is to eliminate the hysteresis controllers and vector selection table commonly found in conventional DTC, addressing associated issues. This innovative strategy relies on Proportional-Integral (PI) controllers and Predictive Control, with both inverters operating at a constant frequency. In the proposed Predictive DTC Control, the predictive model is used to forecast the future behavior of the machine’s torque and current. This allows the control system to make more informed decisions regarding the optimal voltage vectors to apply, minimizing ripples and enhancing the dynamic response. The simulation results, obtained from Matlab/Simulink, demonstrate a significant improvement in the performance of the DSPMSM when using the proposed method. Key metrics such as torque ripple, current ripple, and overall system efficiency were analyzed, showing favorable outcomes compared to conventional DTC methods. The study underscores the potential of predictive control in advancing the performance of DTC systems for DSPMSMs. By leveraging the capabilities of predictive modeling and PI controllers, the proposed method not only addresses the limitations of conventional DTC but also paves the way for more advanced and reliable control strategies in electric drive applications. The findings suggest that the implementation of Predictive DTC Control could lead to more robust and efficient motor drives, which are critical for various industrial applications requiring precise and stable torque control.