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

  • Hamza MediouniEmail author
  • Soumia El Hani
  • Ilias Ouachtouk
  • Mustapha Ouadghiri
  • Imad Aboudrar
Conference paper
Part of the Advances in Science, Technology & Innovation book series (ASTI)


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.


Electric vehicles (EVs) Double-squirrel cage induction motor (DSCIM) Artificial neural networks (ANN) Fuzzy logic (FL) Robustness properties 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Hamza Mediouni
    • 1
    Email author
  • Soumia El Hani
    • 1
  • Ilias Ouachtouk
    • 1
  • Mustapha Ouadghiri
    • 1
  • Imad Aboudrar
    • 1
  1. 1.Energy Optimization, Diagnosis and Control, STIS Center ENSETMohammed V UniversityRabatMorocco

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