Online Identification of PMSM Parameters: Parameter Identifiability and Estimator Comparative Study
Online Identification of PMSM Parameters: Parameter Identifiability and Estimator Comparative Study
复制标题
DOI：
10.1109/tia.2011.2155010
复制
发表时间：
2011-07-01
影响因子：
4.4
通讯作者：
Meibody-Tabar, Farid
中科院分区：
文献类型：
--
作者：
Boileau, Thierry;Leboeuf, Nicolas;Meibody-Tabar, Farid
本文提出了一种基于模型参考的在线辨识方法来估计瞬态和稳态期间的永磁同步电机（PMSM）参数。结果表明，所有参数在稳态下都是不可识别的，必须根据用户的目标进行选择。然后，利用Lyapunov第二法和奇异摄动理论对估计参数的大信号收敛性进行了分析。结果表明，该方法可以与解耦控制技术一起应用，从而提高收敛动态和整体系统稳定性。将该方法与基于扩展卡尔曼滤波器（EKF）的在线识别方法进行比较，结果表明，尽管相对于所提出的方法实现复杂，EKF 并没有给出比所提出的方法更好的结果。它还表明，使用简单的 PMSM 模型使得估计参数对那些应该已知的参数敏感，无论估计器是什么（所提出的方法和 EKF）。在隐极永磁同步电机上实现的仿真结果和实验结果说明了分析方法的有效性并证实了相同的结论。
In this paper, a model-reference-based online identification method is proposed to estimate permanent-magnet synchronous machine (PMSM) parameters during transients and in steady state. It is shown that all parameters are not identifiable in steady state and a selection has to be made according to the user's objectives. Then, large signal convergence of the estimated parameters is analyzed using the second method of Lyapunov and the singular perturbations theory. It is illustrated that this method may be applied with a decoupling control technique that improves convergence dynamics and overall system stability. This method is compared with an extended Kalman filter (EKF)-based online identification approach, and it is shown that, in spite of its implementation complexity with respect to the proposed method, EKF does not give better results than the proposed method. It is also shown that the use of a simple PMSM model makes estimated parameters sensitive to those supposed to be known whatever the estimator is (both the proposed method and EKF). The simulation results as well as the experimental ones, implemented on a non-salient pole PMSM, illustrate the validity of the analytic approach and confirm the same conclusions.