Saad El Fallah

Researcher PHD Student : Battery Management System (BMS) based on Artificial Intelligence at Faculté des Sciences de Fès
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Contact Information
us****@****om
(386) 825-5501
Location
Préfecture de Fès, Fès-Meknès, Morocco, MA

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Experience

    • Morocco
    • Research Services
    • 1 - 100 Employee
    • Researcher PHD Student : Battery Management System (BMS) based on Artificial Intelligence
      • Dec 2020 - Present

      Battery Management System for Electric Vehicles Based on Artificial Intelligence : • SoC estimation of Lithium-ion battery: Simulation and Comparative study of machine learning-based modelling methods. • Deep neural network and artificial neural network models proposed for SoC estimation have been trained for the first time using a combination of experimental and simulation data. • Estimated SoC for high-capacity lithium-ion batteries used in electric vehicles, including 48 Ah and 5.4 Ah batteries. • Simulate several situations, including instantaneous braking and acceleration of electric vehicles, to ensure the reliability of the model used in the accuracy of the SoC estimation, taking into account the effect of the operating temperature in the simulation. • Comparison with the Gated Recurrent Unit Reccurent neural network method, demonstrating the accuracy of the deep neural network in SoC estimation. • Matlab/Simulink software is used to simulate the charge and discharge cycle of a lithium-ion battery cell. • Develop a graphical interface to estimate the SoC more accurately. • Presenting the discharge voltage of a lithium-ion cell used in electric vehicles at different operating temperatures to study the effect of operating temperature on the SoC. • Ensures safety by preventing overcharging or deep discharging of the battery, while enabling correct operation and efficient energy management. • Robust State of Charge Estimation and Simulation of Lithium-ion Batteries Using Deep Neural Network and Optimized Random Forest Regression Algorithm. • Lithium-ion battery state of charge estimation using improved deep recurrent neural network algorithms: simulation results. Show less

    • Motor Vehicle Parts Manufacturing
    • 700 & Above Employee
    • Process Engineer internship - Automotive industry
      • Feb 2020 - Jul 2020

      Missions : • Ensures correct operation of the line. • Analysis of causes and effects impacting line performance (ISHIKAWA). • Improve performance of line (cycle time and effective). • Write documentation for the line (operating procedures, parameter files). • Prepare documents for customer audit. • Plan regular performance meetings. • Participate in process AMDEC. • Application of the DMAIC methodology. • Participate in the elaboration of a plan and a preventive maintenance calendar. Show less

    • Morocco
    • Advertising Services
    • 1 - 100 Employee
    • Applied internship
      • Sep 2019 - Sep 2019

      Missions : • Setting up maintenance ranges. • Data processing. • Machine maintenance. Missions : • Setting up maintenance ranges. • Data processing. • Machine maintenance.

Education

  • Faculté des Sciences de Fès
    Master, Matériaux et applications pour les énergies renouvelables
    2018 - 2020
  • Faculté des Sciences de Fès
    Licence fondamentale, Energétique
    2016 - 2018
  • Faculté des Sciences de Fès
    Deug, Sciences de la Matiere Physique
    2013 - 2016
  • Lycée Moulay Slimane
    Baccalauréat, Sciences Physique
    2012 - 2013

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