Elimination of Harmonic Currents Using a Reference Voltage Vector Based-Model Predictive Control for a Six-Phase PMSM Motor

This paper proposes a novel dead-beat current control (DBCC) based model predictive control for an asymmetrical six-phase permanent magnet synchronous machine (PMSM). First, the solution of DBCC is adopted to obtain the expected reference voltage vector (RVV). Then, two groups of virtual vectors, in the total number of 24 with different magnitudes, are defined for the sake of current harmonics suppression. Subsequently, two in-phase virtual vectors closest to the RVV are selected as the prediction vectors. The next step is to define a cost function which is composed of the error between the RVV and the available prediction vectors. Then, the selected two virtual vectors are evaluated and the one that minimizes the cost function will be applied in the next instant. So, only two prediction vectors need to be evaluated and the computation burden is highly alleviated. The weighting factor involved in predictive torque control is avoided. In addition, to achieve the readily implementation with standard PWM switching sequence, 18 virtual vectors are artfully replaced by their equivalent virtual vectors. Finally, the proposed method is comparatively studied and compared with the conventional model predictive current control method. Experimental results are offered to confirm the effectiveness of the proposed method.