A Flux Constrained Predictive Control for a Six-Phase PMSM Motor With Lower Complexity

This paper proposes a low-complexity model predictive flux control (MPFC) with current harmonics and torque ripple reduced for a six-phase permanent magnet synchronous machine (PMSM) motor. First, the virtual vectors in two different magnitudes are adopted for the sake of harmonic currents and torque ripple reduction, as well as simplifying the predictive model by eliminating the z(1)-z(2) variables fromthe cost function. Then, a look-up table is developed to exclude the useless voltage vectors in advance. In this way, the number of prediction vectors is reduced and heavy computation burden is alleviated. Moreover, to avoid the tedious tuning work of the weighting factor in the cost function, the torque and flux amplitude are transformed into an equivalent reference flux vector. Thus, the complexity of the cost function is significantly reduced. Meanwhile, the current and torque performance are highly improved using the proposed method. Also, the fast dynamic response of predictive control is retained. Finally, simulation and experimental results are offered to verify the effectiveness of the proposed MPFC method.