开关磁阻电机间接检测技术的研究
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摘要
开关磁阻电机(SRM)驱动系统是20世纪80年代迅猛发展起来的一种新型电机驱动系统。SRM以其结构坚固,成本低廉、控制灵活等优点引起人们越来越多的关注,在工业上的应用很有前景。但是SRM物理转子位置传感器的存在影响了电机控制系统的高速性能、可靠性和成本,所以研究转子位置间接检测技术是开关磁阻电机系统研究的重要课题之一。
     本文分析了开关磁阻电机的结构和运行原理,并对国内外的SRM转子位置间接检测技术的研究动态做了详细的整理和分析,同时对两种不同的SRM转子位置间接检测方案进行了重点研究:基于人工神经网络和基于电感模型的间接位置检测方案。
     本文首先研究了基于人工神经网络的SRM转子位置推断方法,文中采用改进的BP算法建立了SR电机神经网络转子位置θ(i,L)模型,从而推断出转子的角位置。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可行。
     本文针对基于电感模型的SRM转子位置检测方法也进行了详细的研究,首先对基于电感模型的间接位置检测技术进行了理论分析,通过实时从被激励相检测电压和电流值,并将其代入动态数学模型,通过解算数学模型就可以获得转子位置信息。本文基于Matlab Simulink建立了基于电感模型的SRM间接位置检测方案的双闭环SRD调速系统的仿真模型,仿真结果表明该方法是切实可行的。
     文中最后介绍了基于TMS320F2812的控制电路、功率电路、检测电路在内的SRM驱动系统的硬件设计以及驱动系统的控制软件设计。
The switched reluctance motor (SRM) drive system has gotten more more attentions because of its excellent characteristics of the firm structure, low cost and flexible control, its application has been limited by the existence of shaft position sensor. the previous schemes of SRD are always equipped with rotor position sensor, which determines the system's high speed performance, reliability and cost. As a result, how to detect the position of non-position sensor rotor has become one major direction in the study of SRD.
     The configuration and fundamental operating principle of SRM are analyzed in the subject. And the latest developments of the same research field both at home and at abroad are well analyzed at the beginning of the dissertation. The same,this subject puts emphasis on the two different detecting methods of non-position sensor rotor,which are based on Artificial Neural Network(ANN) and non-linear inductance model of SRM.
     The detecting method of SRM's rotor position based on Artificial Neural Network(ANN) is first studied in this paper. An ANN rotor position modelθ(i,L) 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.
     In the paper, be directed against of the method, which is based on non-linear inductance model of SRM, which's principle first well is analyzed. The method need active phase currents are measured in real-time and using these measurements, the dynamic equations representing the active phases are solved using numerical techniques in order to obtain rotor position information. The same, it is builded that the system simulation model in the Matlab_Simulink, simulation result is effective.
     The end, the design of the hardware and software of SRM drive system are introduced, including the TMS320F2812 based control circuit, the power drive circuit, the detecting circuit and the control software.
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