在线建模的开关磁阻电机四象限运行无位置传感器控制

基于在线建模提出了一种开关磁阻电机无位置传感器控制方法。建立了以相电流和磁链为输入、转子位置角度为输出的径向基神经网络模型,以轴编码器实时获得的转子位置角度为学习样本,对开关磁阻电机进行了在线建模。提出了静止状态下激励脉冲法与运行状态下滑模观测器相结合的四象限运行无位置传感器控制策略,实现了电机无传感器运行。实验结果表明,电机转子位置估计误差小于2,象限间切换可靠,具有良好的动态和静态性能,为大功率开关磁阻电机无传感器控制提供了一种易于实现的方案。

Four-Quadrant Position Sensorless Control of Switched Reluctance Motors Based on On-Line Modeling

A position sensorless control method based on on-line modeling is presented for switched reluctance motors(SRM).Radial basis function(RBF) neural network of rotor position estimation for sensorless SRM control is established with two input variables: flux linkage and phase current.Real-time rotor position angle obtained from shaft encoder is adopted as learning sample data,and on-line modeling of SRM is realized.Excitation pulse method combined with sliding mode observer(SMO) strategy is proposed and four-quadrant SRM sensorless operation is achieved.Experimental results indicate that rotor position estimation error less than 2° and switching between quadrants is reliable,and the system has good dynamic and static performance.The proposed method is helpful for high-power sensorless control of SRM.