The Fuel cell is main energy source of a Fuel-Cell based electric Vehicle (FCEV).The batteries or Ultra-Capacitors (UC) serves as ancillary source which enhance the vehicle’s performance. The combination of all the components form a Fuel-Cell Hybrid Electric Vehicle (FCHEV), which offers both high energy density and outstanding dynamic response. The controlling system in an FCHEV efficiently manages the power distribution between the FCS, battery, and UC to optimize performance. A key challenge lies in effectively distributing the required power across these sources to maximize the vehicle's efficiency. This paper outlines the design of the powertrain for an FCHEV, incorporating the FCS, battery, and UC. An innovative energy management scheme is developed to improve the vehicle efficiency through FC and UC. The random vector functional link network (RVFLN) is investigated in the fuel cell and ultra-capacitor of the EV. A fuel cell based electric vehicle is designed with a ultra-capacitor in MATLAB/SIMULINK. The model is simulated with the proposed ANN and RVFLN schemes. The proposed scheme improves the power of battery by 18% than ANN. Similarly the UC power increased by 16% as compared to ANN.


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    Titel :

    Improving performance of a fuel-cell hybrid electric Vehicle using Artificial Intelligence based Energy Management System


    Beteiligte:


    Erscheinungsdatum :

    02.05.2025


    Format / Umfang :

    740390 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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