yasser ghoulam | INSA-Strasbourg - Academia.edu (original) (raw)
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National Institute of Technology, Calicut
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Papers by yasser ghoulam
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.
PCIM Europe digital days 2021; International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, May 3, 2021
2022 IEEE Vehicle Power and Propulsion Conference (VPPC)
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...
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.
PCIM Europe digital days 2021; International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, May 3, 2021
2022 IEEE Vehicle Power and Propulsion Conference (VPPC)
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...