【作者】 王燕；

【导师】 王宏华；

【作者基本信息】 河海大学 ， 测试计量技术及仪器， 2003， 硕士

【摘要】 本课题以开关磁阻电动机转子位置间接检测技术为主题开展研究工作，以期有助于无位置传感器SR电机间接检测转子位置技术进一步的研究。 本文在SR电机线性模型和准线性模型基础上给出了一种SR电机的非线性电感模型，采用最小二乘参数估计法给出了该解析表达式的各项系数。 本文研究了基于人工神经网络的SR电机转子位置推断，采用改进的BP算法建立了SR电机神经网络转子位置θ(i，L)模型。由于开关磁阻电机相电感随转子位置变化的非线性，当采用一个神经网络模型时，在电机气隙较大位置处存在较大的误差，因此本文提出采用两个神经网络分段处理。仿真结果表明该方法有效。 本文对基于阻抗法测量相电感的SRM转子位置检测技术进行了仿真研究。根据该方法进行了基于80C196单片机的SRM转子位置间接检测系统的软、硬件设计和调试，初步研究了如何实现无位置传感器SR电机的转子位置间接检测。更多还原

【Abstract】 This subject puts emphasis on the research of position sensorless technique of switched reluctance motor(SRM) for the further development of position sensorless technique of SRM.Based on linear and quasi-linear method, this paper provides a non-linear inductance model of SRM. The coefficients of the model are gained with least square parameter estimation.The deduction method of SRM’s rotor position based on Artificial Neural Network(ANN)is studied in this paper. An ANN rotor position (i, L) model of SRM is built with modified BP neural network. Due to the non-linear influence between phase inductance and rotor position, when a neural network model is used there are more errors where the motor’s air interval is bigger. So this paper suggests to apply two neural networks considering the different situation. Emulation result implies this method is effective.Emulation of detecting rotor position based on resistance method to measure phase inductance is also studied. According to this method a design of software and hardware is presented in this paper ,which uses 196KB single chip as micro controller. How to realize sensorless technique of SRM is studied preliminary.更多还原