The development of novel operational strategies for battery electric trains requires a vehicle model including the traction battery. This paper proposes a method to generate accurate traction battery models on system level for application in a simulation model of battery electric multiple units. Artificial neural networks are used to identify the coherences within real system data from a traction battery used in an electric bus. Two approaches are examined to estimate the terminal voltage: a feedforward neural network and a long short-term memory network. Model generation is followed by a comparison with an existing physics-based battery model in order to prove the increase of accuracy.


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    Titel :

    Modeling of Traction Batteries for Rail Applications Using Artificial Neural Networks


    Beteiligte:
    Bauer, Rene (Autor:in) / Reimann, Sebastian (Autor:in) / Gratzfeld, Peter (Autor:in)


    Erscheinungsdatum :

    21.06.2021


    Format / Umfang :

    888569 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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