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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Modeling of Traction Batteries for Rail Applications Using Artificial Neural Networks


    Contributors:


    Publication date :

    2021-06-21


    Size :

    888569 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Sodium/sulphur batteries for rail traction

    Sudworth, J.L. | Tema Archive | 1975


    Fault detection in 3-phase Traction Motor using Artificial Neural Networks

    Saeid Moosavi, Seyed / Djerdir, A. / Ait-Amirat, Y. et al. | IEEE | 2012


    Application of artificial neural networks to skidder traction performance

    Tohmaz, A.S. / Hassan, A.E. | Tema Archive | 1995


    Application of artificial neural networks to skidder traction performance

    Tohmaz,A.S. / Hassan,A.E. / North Carolina State Univ.,Dep.of Forestry and Biological and Agricultural Engng.,US | Automotive engineering | 1995