An adaptive version of the Kalman Filter (KF) algorithm is investigated as a potential for State of Charge (SOC) estimation in Li-Ion cells. SoC estimation results of the adaptive KF via Battery Management System (BMS) model simulations in MATLAB & Simulink are discussed. The minimal SoC estimation error obtained in the results indicate strong KF adaptability to the complex non-linear cell behavior that typically occurs in active operation, especially in comparison with the Coulomb Counting (CC) current integration, and non-adaptive KF estimation methods.


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    Titel :

    Adaptive Method for Li-Ion Cell State-of-Charge Estimation in Smart Aircraft Applications


    Beteiligte:
    Frierson, Anthony (Autor:in) / Tsao, Bang-Hung (Autor:in) / Zumberge, Nicholas (Autor:in) / Farr, Tim (Autor:in) / Fellner, Joseph (Autor:in) / Herrera, Luis (Autor:in) / Horrocks, Gregory A. (Autor:in)


    Erscheinungsdatum :

    28.08.2023


    Format / Umfang :

    1167201 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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