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One-Dimensional Electromechanical Equivalent Circuit for Piezoelectric Array Elements Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Application of Artificial Intelligence Techniques on Double-Squirrel Cage Induction Motor for an Electric Vehicle Motorization

Authors : Hamza Mediouni, Soumia El Hani, Ilias Ouachtouk, Mustapha Ouadghiri, Imad Aboudrar

Published in: Recent Advances in Electrical and Information Technologies for Sustainable Development

Publisher: Springer International Publishing

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Abstract

Electric Vehicles (EVs) are complex electromechanical systems described by nonlinear models and therefore, their control design and analysis is not an easy task. Double-Squirrel Cage Induction Motor (DSCIM) has the advantages of driving complex loads which require high starting torque and low starting current. This paper presents a speed control comparison between the PI controller and the advanced techniques of control based on the Artificial Neural Networks (ANN) and Fuzzy Logic (FL) in order to be applied for an electric vehicle motorization. The simulation results are numerically validated by using the MATLAB/Simulink universe; they highlight the robustness properties of the different control strategies based on field-oriented control technique.

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previous chapter Study of the Performance of the DRHT and TSP in Delay Tolerant Networks
next chapter Generic Client–Server Interfaces for Real-Time Remote Automatic Control Laboratory
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Metadata
Title
Application of Artificial Intelligence Techniques on Double-Squirrel Cage Induction Motor for an Electric Vehicle Motorization
Authors
Hamza Mediouni
Soumia El Hani
Ilias Ouachtouk
Mustapha Ouadghiri
Imad Aboudrar
Copyright Year
2019
Book
Recent Advances in Electrical and Information Technologies for Sustainable Development

Print ISBN: 978-3-030-05275-1

Electronic ISBN: 978-3-030-05276-8

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-05276-8_16