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Induction Motor Drive Direct Torque Control and Predictive Torque Control Comparison Based on Switching Pattern Analysis

机译:基于开关模式分析的感应电动机驱动直接扭矩控制和预测扭矩控制比较

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摘要

This paper describes a switching pattern generated in case of induction motor drive predictive torque control (PTC) compared to a switching pattern of direct torque control (DTC). PTC is a modern control method for electric drives based on model predictive control (MPC). DTC is a very powerful method and is today an industrial standard for controlling an induction motor drive. Its usage is wide-spread, mainly in high-power applications. However, the method suffers from a few disadvantages. One of the causes of the control method’s problematic behavior is choosing the switching combinations in the flux sector. Another inconvenience is the common selection table not including all voltage vectors in given sector. By these factors, the ripples of flux vector trajectory and torque waveforms are influenced. The longer the sample time is, the more significant the influence of factors becomes, because only a few steps occur within one turn of the magnetic flux vector. Based on the detailed analysis, the reasons of the different performance of both systems are explained. The analysis performed by simulation in Matlab Simulink environment has proved that, while DTC might choose voltage vector that pushes system away from the reference values, the MPC always chooses the most proper vector. The experimental results measured on the real drive confirm the appropriate vector selection, just in case of the predictive control method.
机译:本文描述了与直接扭矩控制(DTC)的切换图案相比,在感应电动机驱动预测扭矩控制(PTC)的情况下产生的切换图案。 PTC是基于模型预测控制(MPC)的电动驱动器的现代控制方法。 DTC是一种非常强大的方法,目前是用于控制感应电机驱动的工业标准。它的使用广泛,主要是在大功率应用中。然而,该方法遭受了几个缺点。控制方法的有问题行为的原因之一是在磁通扇区中选择切换组合。另一种不便是常见的选择表不包括给定扇区中的所有电压矢量。通过这些因素,影响磁通矢量轨迹和扭矩波形的涟漪。采样时间越长,因素的影响越大,因为只有几步发生在磁通量载体的一圈内。基于详细分析,解释了两个系统的不同性能的原因。通过模拟在MATLAB Simulink环境中执行的分析已经证明,当DTC可能选择将系统推开的电压矢量远离参考值,而MPC始终选择最适当的向量。在真实驱动器上测量的实验结果确认了适当的载体选择,即在预测控制方法的情况下。

著录项

  • 作者

    Pavel Karlovsky; Jiri Lettl;

  • 作者单位
  • 年度 2018
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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