Improved Model-Predictive Current Control of Permanent Magnet Synchronous Motor Drives with Designed Cost Function

Model predictive current control (MPCC) is widely applied in electrical drives and power electronics because of its simplicity and efficiency. However, steady-state errors are always present because of the inaccurate prediction induced by changing actual conditions. This paper proposes a simple strategy for improving MPCC performance, which reduces steadystate errors and eliminates the additional prediction compensation. The cost function, which is made up of tracking mistakes, is used in MPCC to choose the best switching state. This paper introduces a new cost function that also includes actual current faults. There is a coefficient of actual current errors that enhances the appropriateness of permanent magnet synchronous motor (PMSM) drives. Experimental results show superior performance of the proposed MPCC to that of conventional MPCC.