An Improved Model-Free Predictive Current Control Method for PMSM Drives Based on Extended Control Set and Fast Current Difference Updating

In recent years, model predictive current control (MPCC) has been widely studied for permanent magnet synchronous motor (PMSM) drives. However, the conventional model predictive control (MPC) method requires an accurate mathematical model. When machine parameters change during operation, the performance of MPC is degraded. To address this issue, model-free predictive current control (MFPCC), which uses only the sampling current, was proposed. The conventional MFPCC approach applies a lookup table (LUT) to store the current difference. However, this technique suffers from stagnant current difference updating (SCDU) due to irregular current spikes, especially at high speeds. Aiming at the poor steady-state performance of traditional MFPCC at high speed, an improved MFPCC method was proposed to PMSM drive. The issue of SDCU is solved by reconstructing all current differences based on the available past information. Additionally, more candidate voltage vectors are constructed by using an extended finite control set. Hence, the steady-state performance is better than that of the conventional MFPCC method, while the dynamic response is unaffected. The proposed method is compared with MPCC and the traditional MFPCC method. Simulation and experimental results show that the proposed method is effective.