A Low-Complexity Three-Vector-Based Model Predictive Torque Control for SPMSM

In conventional model predictive torque control (MPTC), only one voltage vector (VV) is applied during a whole control period, thus causing a large torque ripple. To improve the steady-state performance, some two-vector-based control schemes have been proposed. However, the selection of the optimal VV pair is complex as well as has a large computational burden, and the improvement of performance is still limited by the direction and amplitude of the output VV. This article proposes a low-complexity three-vector-based MPTC for SPMSM drives, which can precisely determine the appropriate active voltage vectors (AVVs) with the predicted torque error. Then, a modified switching table is developed to directly select the AVVs, thus greatly reducing the complexity and computational burden of the algorithm. To obtain a better steady-state performance, a duty cycle calculation method based on torque and stator flux difference parameters is newly proposed to achieve the deadbeat control of torque and stator flux. And then, the experimental comparisons with the double-vector-based MPTC are conducted. The results show that the proposed MPTC can effectively reduce the steady-state torque ripple while maintaining a good dynamic performance as well as almost a fixed switching frequency for all speed ranges.

Automated summary

This study presents a low-complexity three-vector-based MPTC algorithm for SPMSM drives, which can accurately determine the appropriate active voltage vectors and reduce the complexity and computational burden of the algorithm through an improved switching table. By using a duty cycle calculation method based on torque and stator flux difference parameters, deadbeat control of torque and stator flux is achieved.