Artificial Neural Based Speed and Flux Estimators for Induction Machine Drives with Matlab/Simulink

Ahmed A. Zaki Diab, Mohammed A. Elsawy, Kotin A. Denis, Salem Alkhalaf and Ziad M. Ali
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Ahmed A. Zaki Diab: Electrical Engineering Department, Faculty of Engineering, Minia University, Minia 61511, Egypt
Mohammed A. Elsawy: Electrical Engineering Department, Faculty of Engineering, Minia University, Minia 61511, Egypt
Kotin A. Denis: Department of Electric Drive and Automation of Industrial Installations, Novosibirsk State Technical University, 630000 Novosibirsk, Russia
Salem Alkhalaf: Department of Computer, College of Science and Arts in Ar Rass, Qassim University, Ar Rass 58613, Saudi Arabia
Ziad M. Ali: College of Engineering at Wadi Addawasir, Prince Sattam bin Abdulaziz University, Wadi Addawasir 11991, Saudi Arabia

Mathematics, 2022, vol. 10, issue 8, 1-22

Abstract: In this paper, an Artificial Neural Network (ANN) for accurate estimation of the speed and flux for induction motor (IM) drives has been presented for industrial applications such as electric vehicles (EVs). Two ANN estimators have been designed, one for the rotor speed estimation and the other for the stator and rotor flux estimation. The input training data has been collected based on the currents and voltage data, while the output training data of the speed and stator and rotor fluxes has been established based on the measured speed and flux estimator-based mathematical model of the IM. The designed ANN estimators can overcome the problem of the parameter’s variations and drift integration problems. Matlab/Simulink has been used to develop and test the ANN estimators. The results prove the ANN estimators’ effectiveness under various operation conditions.

Keywords: artificial neural network; induction machines drives; speed; flux; estimation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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