Improved Model Based Predictive Torque Control Strategy with Fast Dynamic Response for Flux-Switching Permanent Magnet Machines

The flux-switching permanent magnet machine (FSPMM) has got great attention by academic researchers during the past couple of years for its merits of strong mechanical robustness, high efficiency, strong thermal dissipation ability, etc. However, for its inherited double salient structure in both stator and rotor, the FSPMM suffers from severe torque and flux ripples at different rotor positions for its variable magnetic resistance, which cannot be solved completely only by electromagnetic optimal design. In order to increase the drive performance of FSPMM, such as dynamic response and stable torque smoothness, an improved model based predictive torque control (MPTC) algorithm is proposed. By using the cost function modulation strategy, the torque and flux ripples of FSPMM are reduced evidently, accompanying with the minimized converter switching frequency and power loss. Comprehensive simulation investigations are finally carried out to validate relevant theoretical analysis.