Improved deadbeat predictive current control for PMSM based on PSA parameter identification and weighting factors

The conventional deadbeat predictive current control method for permanent magnet synchronous motor depends on the accuracy of motor parameters, which leads to large current deviation and fluctuation. An improved deadbeat predictive current control method based on the PID search algorithm (PSA) is proposed. With analysis on the mathematical model of the permanent magnet synchronous motor, a current prediction algorithm is introduced to eliminate the one-beat delay in the current command calculation. The weighting coefficients are combined to reduce the current fluctuation and static error. The PSA is utilized to accurately identify the resistance, magnetic chain and inductance parameters. It is to eliminate the current static error caused by parameter mismatch and improve the system robustness. Experiments verify the effectiveness of the proposed method under rated speed and load conditions. The performance of the proposed deadbeat predictive current control method with improved weighting factors is better than that of the conventional method.