基于模型预测开关磁阻电机控制系统研究
[Abstract]:Switched reluctance motor (SRM) has attracted much attention in recent years due to its simple structure, reliable operation, low cost and flexible control. Switched reluctance motor drive system (SRD) has been widely used in many industrial fields, such as mining, oil mining, electric vehicle driving and home appliances. However, due to the structure and control mode of SRM, the torque fluctuation of the motor is large, which limits its application in the field of high-precision control. Therefore, how to effectively reduce SRM torque ripple has gradually become one of the hot research topics of domestic and foreign scholars. Based on the model predictive control method, the switched reluctance motor speed control system is studied in this paper. After analyzing the advantages and disadvantages of the model predictive control method of the finite switch control set, In order to reduce the torque ripple of SRM, the optimized current waveform is predicted and controlled without beat. This paper firstly analyzes and summarizes the research progress in reducing the torque ripple of SRM at home and abroad, and introduces the basic working principle, mathematical equation, general control method and power circuit of SRM. Then, in order to obtain the accurate flux model of the motor, an experimental method to obtain the parameters of the model on line is presented, which is in fact an on-line detection method for the characteristics of the SRM flux chain. In this paper, the error sources of the software flux estimation under static or very low speed conditions are analyzed from the point of view of the controller itself, and the flux estimation is modified according to the proposed equivalent resistance calibration method. Then two specific operation schemes of on-line detection are given, and 18.5k WSRM flux characteristic data are obtained by the open-loop rotational speed scheme. Then a method based on torque minimization to obtain the optimal reference current is introduced, which provides the data support for the later part of the experiment simulation. Then, on the basis of introducing the basic principle and characteristics of Model Predictive Control (MPC), the control system based on finite switch control set model is realized, and the torque ripple, current magnitude and switching frequency of motor are controlled. For the problems of large current fluctuation, unstable switching frequency and high harmonic content in the control system, an improved model predictive control method, that is, model predictive control without beat, is proposed. Based on the optimal current of torque ripple minimization obtained in the previous paper, the non-beat predictive control of reference current is realized to reduce the torque ripple of motor. Finally, this paper introduces the hardware structure and software structure of the control system, and completes the motor operation test based on model prediction through the experimental platform. The experimental results show that the controller can follow the reference current well and restrain the torque ripple in the full speed range. At the same time, the output torque can follow the change of load and speed quickly. The high performance control of the motor is realized, which has certain practicability and reference value.
【学位授予单位】:中国矿业大学
【学位级别】:硕士
【学位授予年份】:2017
【分类号】:TM352;TP273
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