Multiparameter Identification Technique for PMSM Based on Harmonic Coupling Model Considering Torque Ripple Suppression

Accurate online parameter identification is essential to improve the performance of permanent magnet synchronous motor (PMSM). In this paper, a novel multi-parameter identification system based on harmonic coupling model is constructed. The multi-parameter identification can be realized by injecting 11<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> and 13<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> current harmonics. By constructing two extended Kalman filters (EKFs) for fundamental and harmonic model, the system does not have the under-rank problem when identifying PMSM parameters. The system also takes the effects of controller time delay, inverter nonlinearity and PMSM parameter harmonics into consideration. By constructing 11<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> and 13<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> current harmonic coefficient matrix, the influence of harmonic amplitude and matrix condition number on parameter identification is analyzed. Meanwhile, the influence of current harmonics on PMSM torque ripple is considered. By constructing a multi-objective optimization for current harmonics, the parameter identification accuracy and torque ripple suppression are simultaneously improved. The optimized current harmonics have a better effect in identification accuracy compared with harmonics with bigger condition number and have a good effect on torque ripple suppression through simulation and experiment verification.