An Improved Three-Vector-Based Model Predictive Current Control Method for Surface-Mounted PMSM Drives

Abstract

The conventional model predictive control method suffers from large torque ripples and harmonic current. Moreover, the modulation range of output is limited, leading to the deterioration of performance. To address these problems, this article proposes an improved three-vector model predictive current control method for surface-mounted permanent magnet synchronous motor (SPMSM) drives. First, virtual vectors are introduced to increase the number of available voltage vectors, in which the voltage vector control set can be extended. Furthermore, a hierarchical multilevel optimization control algorithm is adopted to obtain the main control set and the extended control set. According to two different control sets, the first and second vectors can be obtained by the cost function, respectively, which can realize modulation range extension. Then, the zero vectors are added to adjust the magnitude of the output voltage vector, and the output vector action time is obtained based on the deadbeat principle. The ripples can be minimized, and the modulation range can be extended with the proposed method. Finally, a comparative analysis of both the simulation and experimental tests is investigated. The comparative investigation verifies the effectiveness and feasibility of the proposed method.