In this paper, energy management strategies (EMS) applied to fuel cell electric vehicles (FCEV) are discussed toward a promising new global architecture. Beyond fuel consumption saving, we aim to improve flexibility to the real-time driving conditions while meeting the constraints of the hybrid energy storage system. To achieve the EMS real-time implementation, vehicle topology and energy sources must first be analyzed. Then, EMS applied to FCEV challenges and constraints can be presented. A classification of the leading existing EMS is established, which explains the relevance for real-time implementation of an integrated EMS (iEMS) architecture based on a hybridization concept, using rule-based, optimization-based, and learning-based strategies simultaneously. Finally, it is shown that data processing algorithms such as driving pattern recognition and driving cycle prediction must also be integrated into real-time driving condition EMS.


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    Title :

    Real-time and multi-layered energy management strategies for fuel cell electric vehicle overview


    Contributors:


    Publication date :

    2022-06-01


    Size :

    543255 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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