Modulated Model-Free Predictive Current Control With Constrained Optimization for Permanent Magnet Synchronous Motor Drives

A new and simple method for synthesizing the optimal voltage for a modulated model-free predictive current control (MMFPCC) algorithm that overcomes the challenges of high current ripple and phase distortions of the conventional finite-set model predictive current controller (FS-MPCC) is presented with implementation for an interior permanent magnet synchronous motor (IPMSM) drive. In this control method, two active vectors and a null voltage vector are used to synthesize the optimal voltage based on the current cost function as opposed to the conventional voltage cost function in conventional deadbeat (DB) MMFPCC. The current cost function minimization is formulated as an optimization problem, and the duty ratio of the voltage vectors are obtained online with reduced computational burden that made implementation for a high-performance motor drive feasible. A competitive analytical solution for the optimization is provided for duty ratio computation. Simulation and experimental results of the proposed method for an IPMSM drive compared with that of a conventional single-vector FS-MPCC and DB MMFPCC at various speeds and loads show superior performance in current tracking, current ripple reduction, and harmonic content suppression.