Identification of electric drive inertia moment on the reaction curve by Simoyu method - Sergey Stelmashchuk (Известия Томского политехнического университета: Инжиниринг георесурсов, 2019)
Relevance of the work is caused by the need to develop the systems with controller auto-tuning for electric drive control systems with variable inertia in a wide range. The main aim of the study is to derive the technique for identifying a drive inertia moment based on data processing of the drive speed reaction curve by Simoyu method. The obligatory condition is the implementation of the techniques by the compute aids based on the control systems. The methods used in the study. The theoretical research was based on the methods of classic control theory and the theory of the electric drive. Practical researches are confirmed by simulation in software environment of MatLAB. The results. The author has developed the technique, which allows determining the inertia moment of the drive using the computer aids in the automatic mode based on the data of drive reaction curve. The application of this technique in the adaptive systems with auto-tuning controller was justified. The author studied the implementation of conditions of the technique and determined that it is more effcient to use the starting characteristic in no-load drive as the reaction curve. The allowable value of the control signal, in which the armature current does not exceed a maximum value, was computed. To prove this technique the author carried out simulation in SimPowerSystems package of MatLAB. It is shown that the above technique is preferable for electric drives with rigid connections in mechanic of the drive, which is a limitation when using the Simoyu method. Conclusions. The developed technique for defining the inertia moment of the electric drive based on the Simoyu areas method allows implementing the identification algorithm of inertia moment in the automatic mode. This will increase the level of technological systems automation by introducing the systems with automatic tuning, which implement the identification algorithm.