开关磁阻电机转矩脉动的智能抑制研究  

Torque Ripple Intelligent Minimization of Switched Reluctance Motor

作　　者：丁文[1] 周会军[1] 鱼振民[1] 

机构地区：[1]西安交通大学,西安710049

出　　处：《微电机》2006年第3期7-10,14,共5页Micromotors

摘　　要：开关磁阻电机的转矩脉动是应用中的一个突出问题。该文对1台6/4极结构的开关磁阻电机在已获得矩角特性的基础上,应用自适应模糊神经网络(ANF IS)对其转矩逆模型进行离线学习。学习完成之后,根据转矩分配函数对各相转矩进行分配,利用模糊神经网络实时优化出期望转矩所需要的相电流波形,然后采用电流滞环跟踪此期望电流,从而实现电机的低转矩脉动控制。仿真结果证明了这种方法的有效性。The torque ripple of switched reluctance motor is a crucial problem in its application fieled. This text uses the adaptive fuzzy-neural networks to the learning of its static torque inverse model off line based on the torque-angle characteristic of a 6/4 structure motor. Then according to the torque distribution function,each phase torque was distributed,and optimal was real-time gained by fuzzy-neural networks on line. At the same time, current hysteretic comparator was utilized to track the current profile,which results in low ripple torque control of switched reluctance motor. The simulation result proves validity of this method.

关 键 词：开关磁阻电动机 自适应控制模糊神经网络 转矩脉动 磁阻电机 

分 类 号：TM352[电气工程—电机]