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Communication Dans Un Congrès Année : 2023

Modeling and Controller Design of Battery/SC Electric Vehicles for Real-time Energy Management

Résumé

This paper deals with a straightforward procedure for modeling and controller design of an electric vehicle with a fully-active hybrid energy storage system comprising the battery and supercapacitor for real-time energy management. Firstly, the dynamic models of the energy storage systems, the average model of bi-directional dc-dc converters, the static model of the electric motor, and the vehicle dynamics are obtained. Then, a classical low-pass filter is employed as a supervisory control to define the reference signals of the low-level controllers, which aim to regulate the input currents of the bi-directional dc-dc converters. Besides, the dc-dc converters efficiency factor, depending on the converter power flow direction and operating point, is considered in the electric vehicle model. Next, the obtained model is validated using the FTP-75 drive cycle by comparing the results with an electric vehicle of the commercial CarSim software. Finally, the developed electric vehicle model is implemented in dSPACE using a recent WLTC drive cycle to verify its performance in a real-time digital simulator. The obtained results demonstrate the effectiveness of the proposed modeling approach for real-time energy management in battery/SC electric vehicles.
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Dates et versions

hal-04281586 , version 1 (13-11-2023)

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Morteza Rezaei Larijani, Shahin Hedayati Kia, Mohammadreza Zolghadri, Ahmed El Hajjaji, Amir Taghavipour. Modeling and Controller Design of Battery/SC Electric Vehicles for Real-time Energy Management. 2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring), Jun 2023, Florence, Italy. pp.1-7, ⟨10.1109/VTC2023-Spring57618.2023.10199413⟩. ⟨hal-04281586⟩
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