基于动态折息因子递推最小二乘法的 永磁同步电机参数辨识

针对传统递推最小二乘法（RLS）辨识永磁同步电机（PMSM）参数精度较差问题，提出了一种动态折息RLS的PMSM参数辨识方法。在PMSM数学模型基础上建立了多参数辨识模型，实现了多参数实时辨识；对RLS引入动态折息因子，通过估计误差对其实时调整，克服了传统RLS数据饱和与估计精度较差问题。仿真分析和实验结果表明，在不同工况下，所提方法在辨识电机定子电阻、定子电感和永磁磁链参数的误差均控制在1%以内，比传统参数辨识方法具有更好的辨识精度与快速性。

PMSM Parameter Identification Based on the Dynamic Discount Factor Recursive Least Square Method

In view of the problem of poor accuracy of traditional recursive least square (RLS) method for PMSM parameter identification, a dynamic discount RLS method has thus been proposed for PMSM parameter identification. On the basis of PMSM mathematical model, a multi-parameter identification model is established to realize a real-time multi-parameter identification; with the dynamic discount factor introduced to RLS, the real time adjustment of estimation error helps to overcome the problems of traditional RLS data saturation and poor estimation accuracy. The simulation analysis and experimental results show that under different working conditions, the error of the proposed method in identifying motor stator resistance, stator inductance and permanent magnet flux parameters can be controlled within 1%, which is more improved than the traditional parameter identification methods in identification accuracy and rapidity.