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Online Equivalent Circuit Parameter Estimation of Three-Phase Induction Motor Using ANN

  • D. K. ChaturvediEmail author
  • Mayank Pratap Singh
Original Contribution

Abstract

Three-phase induction motor is compact, robust and simple in construction. An accurate estimation of parameters is always required for precise control and monitoring of three-phase induction motor. There are many ways to find the induction motor parameters, but to improve the accuracy of them, the neural approach is used in this paper. The GNN used for online estimation of delta-connected induction motor parameters is presented, and the results are compared with ANN. Experimental setup is developed in Electrical Power Research Lab at Dayalbagh Educational Institute, Agra, U.P., India, which consists of a 415-V, 50-Hz, three-phase squirrel-cage induction motor, belt-pulley loading system, voltage-, current- and power-measuring sensors, three-phase autotransformer, data acquisition system and online parameter estimator. The sensor data are used to estimate induction motor parameters online using neural approach.

Keywords

Parameter estimation Three-phase induction motor GNN Artificial neural networks (ANNs) Equivalent circuit parameters Soft computing techniques 

List of Symbols

r1

Series resistance of stator side (ohm)

x1

Series reactance of stator side (ohm)

r2

Effective series resistance of rotor referred to stator side

x2

Effective series reactance of rotor referred to stator side

Notes

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Copyright information

© The Institution of Engineers (India) 2019

Authors and Affiliations

  1. 1.Department of Electrical Engineering, Faculty of EngineeringDayalbagh Educational InstituteDayalbagh, AgraIndia

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