Multivector-Based Model Predictive Control With Geometric Solution of a Five-Phase Flux-Switching Permanent Magnet Motor

To enhance the steady-state performance of the virtual-vector-based model predictive current control (VV-MPCC) for a five-phase flux-switching permanent magnet motor, an improved multi-vector-based MPCC (MV-MPCC) method with geometric solution is proposed and investigated in this article. The desired voltage is employed to preselect voltage vector candidates and provide a guidance for the geometric division of a sector. According to the link between the reference voltage and the division, the optimal voltage vectors are determined and their duty ratios are obtained by projection method. Compared to the conventional MV-MPCC method using derivative method, the proposed geometric MV-MPCC method employs the desired voltage to quickly determine the voltage vectors and the corresponding duty ratio, which not only alleviates computational burden but also favors for more intuitive implementation. Finally, the effectiveness of the proposed method is verified by experiments.