永磁同步电动机非线性参数模型

Nonlinear Parameter Model of PMSMs

为了得到永磁同步电动机参数非线性特性,设计了永磁同步电动机的负载实验,得到不同负载条件下电机的输入输出特性,再结合控制模型采用预报误差的参数估计算法,对电机的主要参数进行了估计计算,得到参数神经网络模型的训练样本,经学习得到四个参数的非线性神经网络模型,经过仿真验证,得到的参数模型能准确体现电机参数的非线性特性,该模型可用于永磁同步电动机控制系统的参数在线辨识。

To gain the nonlinear parameter characteristics of PMSMs, the load test was performed and the input and out- put characteristics under different load conditions were obtained. With the control model, the parameter estimating algorithm using prediction error was carried out to calculate the major parameters, resulting in four training samples of the parameter neural network model. Simulation results show that the proposed model can effectively and accurately describe the nonlinear characteristics of motor parameters. It can be used for the on-line identification of the PMSM control system.