基于改进最小二乘法永磁同步电机多参量辨识

针对永磁同步电机(PMSM)多参量辨识数学模型欠秩的情况,将电机参数分为快变化和慢变化2种类型参数,结合慢参量入口和电机稳态信息建立慢辨识模型和快辨识模型,提出了一种改进的分步迭代在线辨识方法。该方法基于电机在旋转坐标系下的稳态电压方程,分时分步固定慢变化参数,利用遗忘因子递推最小二乘算法,能够辨识表贴式永磁同步电机(SPMSM)的3个电气参数,计算压力小,辨识速度快,适于工程应用。以DSP控制器和测功机试验平台为基础的试验证明了辨识方法的可行性。

Multi-Parameter Identification of Permanent Magnet Synchronous Motor Based on Improved Least Square Method

In view of the low rank of the multi-parameter identification mathematical model of permanent magnet synchronous motor (PMSM), the motor parameters are divided into two types: fast change and slow change. The slow identification model and fast identification model are established by combining the slow parameter entry and the steady-state information of the motor, and a step-by-step iterative online identification method is proposed. Based on the steady-state voltage equation of the motor in the rotating coordinate system, the slowly changing parameters is fixed in time and step by step. The forgetting factor recursive least square algorithm can identify the three electrical parameters of the surface permanent magnet synchronous motor (SPMSM). It has small calculation pressure and fast identification speed, which is suitable for engineering application. Experiments are performed based on DSP controller and dynamometer test platform. The experimental results prove that the identification method is feasibility.