基于多项式磁饱和模型及EKF的感应电机磁链观测

摘要

Rotor flux is an important parameter in vector control of induction motor.The flux is usually estimated from measured three-phase current,which is often being influenced by noise.The accuracy of observer is related with motor parameters.If the flux level varies with motor working points,the nonlinear magnetic saturation effect will cause variation of mutual inductance.Then,the amplitude and position of rotor flux will deviate from real value,deteriorating the control performance.In this paper,observer algorithm for state estimation and parameter identification,based on extended Kalman Filter (EKF) and forth-order polynomial magnetic saturation model,is proposed.The stator current works as feedback,to correct the predicted value from induction motor model.The simulation and experimental results show the effectiveness of the proposed algorithm in reducing the influence of magnetic nonlinear effect on control system.%感应电机的转子磁链通常用定子电流进行观测,易受测量噪声影响,且观测模型精度与电机参数有关.当电机内磁场幅值变化时,磁路非线性饱和效应会引起互感参数波动,导致观测磁链的幅值和方向偏离实际值,使控制出现偏差.对此,提出基于四阶多项式磁饱和模型以及扩展卡尔曼滤波(EKF)的全状态估计算法,以定子电流作为反馈,观测转子磁链的同时,辨识互感参数.仿真及实验结果表明所提算法能降低磁饱和非线性对控制系统的影响.