Multi-Vector-Based Model Predictive Torque Control for a Six-Phase PMSM Motor With Fixed Switching Frequency

Abstract

This paper proposes a multi-vector-based model predictive torque control with fixed switching frequency for a six-phase permanent-magnet synchronous machine to improve its steady-state performance. First, two active vectors are synthesized in each control period to suppress the stator current harmonics in x-y subspace. For the sake of easy implementation in the real-time system, the vectors are artfully synthesized in two different manners. Second, to achieve the fixed switching frequency, two null vectors are inserted along with the synthesized vector. The duty ratio of the null vectors is determined based on the principle of deadbeat torque control. In the meantime, the synthesized vector and its duty ratio are evaluated simultaneously by the cost function. In this way, the torque ripple can be reduced considerably. Thus, with the proposed method, both the current harmonics and the torque ripple are reduced effectively. Also, the proposed methodology can be readily implemented practically under the constant switching frequency. Finally, the experimentation is carried out to verify the validity of the proposed method.