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Demba Diallo

Demba Diallo

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
35
Citations
7458
World Ranking
5458
National Ranking
108

Overview

Demba Diallo is affiliated with CentraleSupélec in France and has conducted extensive research primarily in the field of engineering. Their scholarly work focuses on several subfields including Electrical and Electronic Engineering, Control and Systems Engineering, Renewable Energy, Sustainability and the Environment, Automotive Engineering, and Mechanical Engineering.

The scientist's research covers a series of topics centered on energy systems, fault diagnosis techniques, and optimization processes. Key topics of study include:

  • Machine Fault Diagnosis Techniques
  • Photovoltaic System Optimization Techniques
  • Advanced Battery Technologies Research
  • Microgrid Control and Optimization
  • Fault Detection and Control Systems
  • Multilevel Inverters and Converters
  • Advancements in Battery Materials

Their recent papers illustrate a concentrated interest in photovoltaic technology, fault diagnosis, and battery management systems. Some of the recent publications include:

  • Application of Artificial Neural Networks to photovoltaic fault detection and diagnosis: A review (2020), Renewable and Sustainable Energy Reviews
  • Fault diagnosis of photovoltaic panels using full I-V characteristics and machine learning techniques (2021), Energy Conversion and Management
  • A Degradation Empirical-Model-Free Battery End-of-Life Prediction Framework Based on Gaussian Process Regression and Kalman Filter (2022), IEEE Transactions on Transportation Electrification
  • A review of current issues of marine current turbine blade fault detection (2020), Ocean Engineering
  • Incipient short-circuit fault diagnosis of lithium-ion batteries (2020), Journal of Energy Storage

Demba Diallo has published multiple papers in several frequent venues, including:

  • Energy Conversion and Management
  • IEEE Transactions on Transportation Electrification
  • Ocean Engineering
  • Control Engineering Practice
  • IEEE Access

Collaboration is an important aspect of their research activities. Some of the most frequent co-authors they have worked with are:

  • Claude Delpha
  • Tianzhen Wang
  • Anne Migan-Dubois
  • Jianwen Meng
  • Baojie Li

Best Publications

  • Electric Motor Drive Selection Issues for HEV Propulsion Systems: A Comparative Study

    M. Zeraoulia;M.E.H. Benbouzid;D. Diallo

  • A Loss-Minimization DTC Scheme for EV Induction Motors

    A. Haddoun;M.E.H. Benbouzid;D. Diallo;R. Abdessemed

  • A Fuzzy-Based Approach for the Diagnosis of Fault Modes in a Voltage-Fed PWM Inverter Induction Motor Drive

    F. Zidani;D. Diallo;M. El Hachemi Benbouzid;R. Nait-Said

  • Fault detection and diagnosis in an induction Machine drive: a pattern recognition approach based on concordia stator mean current vector

    D. Diallo;M.E.H. Benbouzid;D. Hamad;X. Pierre

  • A fault-tolerant control architecture for induction motor drives in automotive applications

    D. Diallo;M.E.H. Benbouzid;A. Makouf

  • Advanced Fault-Tolerant Control of Induction-Motor Drives for EV/HEV Traction Applications: From Conventional to Modern and Intelligent Control Techniques

    M.E.H. Benbouzid;D. Diallo;M. Zeraoulia

  • Induction motor stator faults diagnosis by a current Concordia pattern-based fuzzy decision system

    F. Zidani;M.E.H. Benbouzid;D. Diallo;M.S. Nait-Said

  • A loss-minimization DTC scheme for EV induction motors

    A. Haddoun;M.E.H. Benbouzid;D. Diallo;R. Abdessemed

  • Design of a Fault-Tolerant Controller Based on Observers for a PMSM Drive

    Ahmad Akrad;Mickaël Hilairet;Demba Diallo

  • Incipient fault detection and diagnosis based on Kullback-Leibler divergence using principal component analysis

    Jinane Harmouche;Claude Delpha;Demba Diallo

  • Modeling, Analysis, and Neural Network Control of an EV Electrical Differential

    A. Haddoun;M. El Hachemi Benbouzid;D. Diallo;R. Abdessemed

  • Incipient fault detection and diagnosis based on Kullback–Leibler divergence using Principal Component Analysis: Part I

    Unknown

  • Improved Fault Diagnosis of Ball Bearings Based on the Global Spectrum of Vibration Signals

    Jinane Harmouche;Claude Delpha;Demba Diallo

  • Two Active Fault-Tolerant Control Schemes of Induction-Motor Drive in EV or HEV

    A. Raisemche;M. Boukhnifer;C. Larouci;Demba Diallo

  • An optimal fault detection threshold for early detection using Kullback-Leibler Divergence for unknown distribution data

    Abdulrahman Youssef;Claude Delpha;Demba Diallo

  • A robust hybrid current control for permanent-magnet synchronous motor drive

    M. Kadjoudj;M.E.H. Benbouzid;C. Ghennai;D. Diallo

  • PMSM Drive Position Estimation: Contribution to the High-Frequency Injection Voltage Selection Issue

    Slimane Medjmadj;Demba Diallo;Mohammed Mostefai;Claude Delpha

  • Fault diagnosis of photovoltaic panels using full I–V characteristics and machine learning techniques

    Baojie Li;Claude Delpha;Anne Migan-Dubois;Demba Diallo

  • An imbalance fault detection method based on data normalization and EMD for marine current turbines.

    Milu Zhang;Tianzhen Wang;Tianhao Tang;Mohamed Benbouzid

  • Direct torque control of induction motor with fuzzy stator resistance adaptation

    F. Zidani;D. Diallo;M.E.H. Benbouzid;R. Nait-Said

  • A review of current issues of marine current turbine blade fault detection

    Tao Xie;Tianzhen Wang;Qianqian He;Demba Diallo;Demba Diallo

  • FDI based on Artificial Neural Network for Low-Voltage-Ride-Through in DFIG-based Wind Turbine.

    Amel Adouni;Dhia Chariag;Demba Diallo;Mouna Ben Hamed

  • Electric motor drive selection issues for HEV propulsion systems: a comparative study

    M. Zeraouila;M.E.H. Benbouzid;D. Diallo

Frequent Co-Authors

Mohamed Benbouzid
Mohamed Benbouzid University of Western Brittany
Romeo Ortega
Romeo Ortega Instituto Tecnológico Autónomo de México
Gerard-Andre Capolino
Gerard-Andre Capolino University of Picardie Jules Verne

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