A Simplified Virtual-Vector-Based Model Predictive Control Technique With a Control Factor for Three-Phase SPMSM Drives

Compared with the single-vector-based model predictive control (MPC) technique, the multiple-vector-based MPC technique gains interests in improving the total harmonic distortion (THD) of the stator currents and reducing electromagnetic torque and stator flux ripples for a three-phase surface permanent magnet synchronous motor (SPMSM). However, the complicated enumeration and operation in vector selection and duty cycle calculation increase the computational burden and limit its penetration. Hence, in this article, a simplified virtual-vector-based MPC with a control factor for a three-phase SPMSM is proposed. Without sector identification and enumeration operations, the proposed technique utilizes the control factor to automatically generate a large number of virtual vectors to achieve equivalent performance effectiveness with a multiple-vector-based MPC technique with a lower sampling frequency. Subsequently, regardless of the number of virtual vectors, the candidate virtual vectors are directly identified in an $x-y$ coordinate system to greatly reduce the computational burden. In addition, the duration of the selected optimal virtual vector and the resultant switching sequences are easily obtained and arranged to even the switching losses among the switching devices and further optimize the THD of the stator current. The proposed technique is simplified and flexible. Its control effectiveness is verified by experimental results.