yasser ghoulam | INSA-Strasbourg - Academia.edu (original) (raw)

yasser ghoulam

Related Authors

Beat Signer

Càndid Reig

Marc Champagne

Remo Caponi

Armando Marques-Guedes

John Sutton

Lyla B Das

Lyla B Das

National Institute of Technology, Calicut

Ezequiel  Di Paolo

Fabio Cuzzolin

Lyudmila S Mihaylova

Uploads

Papers by yasser ghoulam

Research paper thumbnail of Modeling, Identification and Simulation of Hybrid Battery/Supercapacitor Storage System Used in Vehicular Applications

Energy storage system would play a crucial role in the electric and hybrid vehicle applications. ... more Energy storage system would play a crucial role in the electric and hybrid vehicle applications. This paper presents modeling, identification and validation of the behavior of two energy storage devices, battery and supercapacitor, used for a hybrid energy storage system (HESS) in electric vehicle applications. Besides of both main storage elements, the HESS includes bi-directional DC/DC power converters suitable for power electronic interface between the battery main energy storage system and the supercapacitor. Design and modeling of the DC/DC power converter is discussed in this study. The electric state-space models of both power sources, battery and supercapacitor, are also developed. And following that lead, the identification of both storage components constituting the HESS is carried out via many optimization methods based on laboratory experimental data of an urban electric vehicle. The obtained results show the good performance of the state space developed models comparing with the experimental results from a test bench developed in our laboratory.

Research paper thumbnail of Electro-Thermal Battery Model for Automotive Applications

PCIM Europe digital days 2021; International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, May 3, 2021

Research paper thumbnail of Energy Management Strategy with Adaptive Cut-off Frequency for Hybrid Energy Storage System in Electric Vehicles

2022 IEEE Vehicle Power and Propulsion Conference (VPPC)

Research paper thumbnail of Lithium-Ion Battery Parameter Identification for Hybrid and Electric Vehicles Using Drive Cycle Data

Energies

This paper proposes an approach for the accurate and efficient parameter identification of lithiu... more This paper proposes an approach for the accurate and efficient parameter identification of lithium-ion battery packs using only drive cycle data obtained from hybrid or electric vehicles. The approach was experimentally validated using data collected from a BMW i8 hybrid vehicle. The dual polarization model was used, and a new open circuit voltage equation was proposed based on a simplification of the combined model, with the aim of reducing the number of parameters to be identified. The parameter identification was performed using NEDC data collected on a rolling road dynamometer; the results showed that the proposed model improved the accuracy of terminal voltage estimation, reducing the peak voltage error from 2.16% using the Nernst model to 1.28%. Furthermore, the robustness of these models in maintaining accuracy when new drive cycles were used was evaluated by comparing WLTC simulations with experimental measurements. The proposed model showed improved robustness, with a reduc...

Research paper thumbnail of Identification des paramètres d'un modèle de batterie lithium-ion pour une source hybride de véhicule électrique

Research paper thumbnail of Modeling, Identification and Simulation of Hybrid Battery/Supercapacitor Storage System Used in Vehicular Applications

Energy storage system would play a crucial role in the electric and hybrid vehicle applications. ... more Energy storage system would play a crucial role in the electric and hybrid vehicle applications. This paper presents modeling, identification and validation of the behavior of two energy storage devices, battery and supercapacitor, used for a hybrid energy storage system (HESS) in electric vehicle applications. Besides of both main storage elements, the HESS includes bi-directional DC/DC power converters suitable for power electronic interface between the battery main energy storage system and the supercapacitor. Design and modeling of the DC/DC power converter is discussed in this study. The electric state-space models of both power sources, battery and supercapacitor, are also developed. And following that lead, the identification of both storage components constituting the HESS is carried out via many optimization methods based on laboratory experimental data of an urban electric vehicle. The obtained results show the good performance of the state space developed models comparing with the experimental results from a test bench developed in our laboratory.

Research paper thumbnail of Electro-Thermal Battery Model for Automotive Applications

PCIM Europe digital days 2021; International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, May 3, 2021

Research paper thumbnail of Energy Management Strategy with Adaptive Cut-off Frequency for Hybrid Energy Storage System in Electric Vehicles

2022 IEEE Vehicle Power and Propulsion Conference (VPPC)

Research paper thumbnail of Lithium-Ion Battery Parameter Identification for Hybrid and Electric Vehicles Using Drive Cycle Data

Energies

This paper proposes an approach for the accurate and efficient parameter identification of lithiu... more This paper proposes an approach for the accurate and efficient parameter identification of lithium-ion battery packs using only drive cycle data obtained from hybrid or electric vehicles. The approach was experimentally validated using data collected from a BMW i8 hybrid vehicle. The dual polarization model was used, and a new open circuit voltage equation was proposed based on a simplification of the combined model, with the aim of reducing the number of parameters to be identified. The parameter identification was performed using NEDC data collected on a rolling road dynamometer; the results showed that the proposed model improved the accuracy of terminal voltage estimation, reducing the peak voltage error from 2.16% using the Nernst model to 1.28%. Furthermore, the robustness of these models in maintaining accuracy when new drive cycles were used was evaluated by comparing WLTC simulations with experimental measurements. The proposed model showed improved robustness, with a reduc...

Research paper thumbnail of Identification des paramètres d'un modèle de batterie lithium-ion pour une source hybride de véhicule électrique

Log In