Research of parameter identification of permanent magnet synchronous motor on line

• Published in: Dianji yu Kongzhi Xuebao = Electric Machines and Control no. 3
• Main Authors: Shi, Jian-fei, Ge, Bao-jun, Liu, Yan-ling, Han, Ji-chao
• Format: Journal Article
• Language: Chinese; English
• Published: Harbin Harbin University of Science and Technology 01.03.2018
• Subjects: Accuracy; Algorithms; Computer simulation; Convergence; Economic models; Least squares; Mathematical models; Noise; Parameter estimation; Parameter identification; Permanent magnets; Process parameters; Robustness (mathematics); Synchronous motors; White noise
• ISSN: 1007-449X
• DOI: 10.15938/j.emc.2018.03.003

In the process of parameter identification of permanent magnet synchronous motor,due to the influence of data saturation and noise,the traditional recursive least squares has the problems of high error and slow convergence in the parameter estimation. Using the improved recursive least squares algorithm can improve the identification accuracy and rate of convergence,thus meet the dynamic performance of servo system under different working conditions. First of all,combined with the mathematical model of the permanent magnet synchronous motor,a discount recursive least squares identification algorithm was designed,and the flexibility of the algorithm was enhanced by introducing the "discount factor"in the traditional recursive least square. Then,dynamic simulation of identification algorithm was finished of the motor with white noise model. Finally,experiments were carried out using the experimental test platform. The simulation and experimental results show that the discount recursive least squares algorithm effectively reduce the influence of old data on the identification results and enhances the robustness to noise interference,and improves the accuracy of parameters identification and real time.