开关磁阻电机磁链转矩观测器的研究

发布时间：2018-05-17 23:30

本文选题：开关磁阻电机 + 磁链观测器　；参考：《大连海事大学》2017年硕士论文

【摘要】：开关磁阻电机调速系统凭借着优异的调速性能、简单的结构、可靠的运行特性等诸多优势,引起了国内外研究学者的广泛关注而直接转矩控制由于具有系统简洁、鲁棒性强、动静态性能良好等优点,也逐步在开关磁阻电机调速系统中得到了应用。但是,传统的直接转矩控制技术也存在一些需要改进的方面,比如转矩脉动较大、磁链观测不精确、开关频率不固定等,影响了系统的整体性能。本文主要在定子磁链观测器和转矩观测器这两方面进行了深入的研究,针对磁链观测器与转矩观测器的不足,提出了新的磁链观测方法和转矩观测方法。针对传统直接转矩控制中磁链观测器与转矩观测器计算不准的缺陷,分别运用有限元分析与BP神经网络技术两种方法建立磁链观测器与转矩观测器。第一种方法运用有限元软件对开关磁阻电机进行建模,使用建模得到的磁链特性曲线与转矩特性曲线建立磁链观测器与转矩观测器。第二种方法是利用BP神经网络建立磁链观测器,为了提高BP神经网络的精度,应用了粒子群算法优化BP神经网络,建立了基于粒子群优化的BP神经网络磁链观测器。在MATLAB仿真平台上,首先,对基于有限元分析的磁链观测器与转矩观测器进行了仿真分析,其次,对基于BP神经网络的磁链观测器进行了仿真分析。仿真结果表明,两种方法确实提高了磁链观测器与转矩观测器的精度。最后,将这两种方法建立的磁链观测器作对比,为两种方法的后续研究打下了基础。
[Abstract]:The switched reluctance motor speed control system, with its excellent speed regulation performance, simple structure and reliable operating characteristics, has aroused wide attention of researchers at home and abroad and direct torque control has the advantages of simple system, strong robustness, good dynamic and static performance and so on, and also gradually obtained in the switched reluctance motor speed control system. However, there are some improvements in the traditional DTC technology, such as the torque ripple, the inaccuracy of the flux linkage observation, the unfixed switching frequency and so on, which affect the overall performance of the system. In this paper, the two aspects of the stator flux observer and torque observer are studied in this paper, and the flux view is focused on the flux view. A new magnetic chain observation method and a torque observation method are proposed for the shortage of the torque observer and the torque observer. In view of the defect that the flux observer and the torque observer are not accurate in the traditional direct torque control, two methods of the flux observer and the torque observer are established by the finite element analysis and the BP neural network. The first method is used to carry out the flux observer and torque observer. The finite element software is used to model the switched reluctance motor. The flux observer and torque observer are established by using the characteristic curve of the magnetic chain and the torque characteristic curve. The second method is to establish the flux observer by BP neural network. In order to improve the precision of the BP neural network, the particle swarm optimization algorithm is used to optimize the BP neural network. The BP neural network flux observer based on particle swarm optimization is used. On the MATLAB simulation platform, first, the magnetic chain observer and torque observer based on finite element analysis are simulated and analyzed. Secondly, the magnetic chain observer based on BP neural network is simulated and analyzed. The simulation results show that the two methods do improve the flux linkage observation. The accuracy of the observer and the torque observer is compared. Finally, the comparison of the flux observer constructed by these two methods lays the foundation for the subsequent research of the two methods.
【学位授予单位】：大连海事大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM352

【相似文献】