Lithium battery is widely used in recent years. In this paper, an improved battery model combined with the equivalent circuit model and the electrochemical model is established. The main efforts of our study are: Firstly, the Ohmic resistance of the battery model is identified online based on the Unscented Kalman Filtering (UKF) algorithm. Secondly, the estimation model of the State of Health (SOH) for the 18650-type battery is established. Thirdly, an improved battery SOH estimation method based on UKF algorithm is proposed. The experimental results indicate that our new battery model considers the different value of the battery internal resistance on the different working condition, like the different voltage, the different current and the different temperature.


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    Titel :

    The Application of UKF Algorithm for 18650-type Lithium Battery SOH Estimation


    Beteiligte:
    Chen, Zhao-Ping (Autor:in) / Wang, Qiu-Ting (Autor:in)


    Erscheinungsdatum :

    2014


    Format / Umfang :

    6 Seiten




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch