Effective Multivector-Operated Predictive Current Control of PMSM Drive With Reduced Torque and Flux Ripple

Model predictive current control (MPCC) is a frequently used method for the control of permanent magnet synchronous motor (PMSM). It has faster execution on the modern digital platform than the previous generation microcontrollers. Conventional MPCC (C-MPCC) fails to provide satisfactory steady-state performance as a single voltage vector (VV) is applied during every sampling interval. This article proposes two novel multivector-operated MPCC methods for reducing torque and flux ripples, as well as the computational burden. The first proposed method uses one active and one null VV, whereas the second method uses two active and one null VVs to further improve the steady-state performance. Proposed methods determine the required change in stator-flux (CSF) to reduce/eliminate error in stator-current during every sample and VVs nearer to the CSF vector are chosen as optimal VVs. The duration of optimal VVs is calculated using the components of CSF along optimal VVs. CSF, obtained using calculated durations of optimal VVs, significantly reduces torque and flux ripples. The proposed methods are effective and less complex compared to other multivector-operated methods. The proposed methods are compared with existing two-VV and three-VV-based MPCC methods and their effectiveness is experimentally verified for decreased torque and stator-flux ripple in addition to a small rise in switching frequency.