부산대학교 도서관

Multiphase machines are increasingly used in research and industry applications due to their inherent advantages. Stator current control is a common strategy for this type of systems. The most important issue it must face is regulation of currents in the torque producing plane and the harmonic plane. For this task, finite control set model predictive control (FCS-MPC) constitutes an interesting alternative to methods using modulation. However, the implementation of FCS-MPC is characterized by a high computational demand, limiting the sampling frequency. This work proposes a predictive algorithm that needs less computation time. As a result, the sampling period can be reduced while producing predictive control. This brings about several benefits resulting from improved current tracking. The proposed method avoids the combinatorial optimization phase of standard FCS-MPC, which is the most time-consuming part. The algorithm is based on physical insights obtained from the application of FCS-MPC to multiphase drives leading to the concept of evolutionary gaps regions. The experimental results for a five-phase motor demonstrate improved performance. Moreover, the method is flexible enough to balance the tradeoff appearing between the torque producing plane and the harmonic plane.