DREM-Based Parameter Estimation Method for MPCC Controlled IPMSM with Voltage Smoother

Abstract

Model predictive current control (MPCC) is a fast and accurate current control method for interior permanent magnet synchronous motors (IPMSMs), which controls the current on the basis of current values predicted using a mathematical model of the IPMSM. MPCC requires accurate motor parameters, and a parameter estimation using a current ripple caused by MPCC has been proposed. As this ripple causes acoustic noise and vibration, a voltage smoother has recently been proposed to suppress the ripple. High-performance current control necessitates an appropriate combination of both parameter estimation and voltage smoothing; however, combining them is difficult. Suppression of the current ripple makes parameter estimation difficult. Therefore, a novel estimation method based on dynamic regressor extension and mixing (DREM) is proposed for realizing high-performance current control in MPCC-controlled IPMSM. Experimental results demonstrate the validity of the proposed approach.