摘要
本文提出了一种永磁同步电动机参数在线辨识的新方法。通过对永磁同步电动机在d-q坐标系下,标准最小二乘法形式的参数辨识模型的推导,利用带遗忘因子最小二乘法(FFRLS)对电动机定子电阻值和交直轴电感值进行在线辨识,借助以上辨识结果,采用模型参考自适应方法(MRAS)再辨识出电动机的永磁磁链。同时应用基于Popov超稳定性理论设计的PI自适应律,实现各种工况下电动机的永磁磁链在线辨识。以一台0.75kW永磁同步电动机为例进行了仿真与实验研究,仿真结果显示,该方法具有计算量较小、准确度较高且具有较佳的动态跟踪辨识特性。
A new method of on-line parameters identification of Permanent Magnet Synchronous Motor（PMSM） is proposed in this paper. The parameter identification model of PMSM in the d-q coordinate system is deduced according to the standard form of least squares method. The Forgetting Factor Recursive Least Square（FFRLS） is used to identify stator resistance value and direct axis and quadrature axis inductance value online. Based on the above identification results, the Model Reference Adaptive System（MRAS） is used to identify the permanent magnet flux linkage of the motor. The PI adaptive law based on design of Popov hyperstability theory is used to realize the on-line identification of permanent magnet flux linkage of the motor under various operating conditions. Finally, the simulation and experiment are developed with a 0.75 kW PMSM as an example. The simulation results show that the proposed method in this paper has the advantages of less computation, high accuracy and better dynamic tracking performance.
出处
《电气技术》
2017年第11期91-95,共5页
Electrical Engineering
