State-of-Power (SoP) prediction of Li-ion battery is necessary in battery management system for electric vehicles in order to deal with limited conditions, prevent overcharge and over discharge situations, increase the life of the battery and provide effective battery operation. This article suggests a method to on-line predict the 10-s charge and discharge peak power of Li-ion battery by twice recursions. First with the dynamic battery model we use the first recursion based on a least square method to get parameters which are influenced by the state of charge of Li-ion battery and temperature, etc. The dynamic model is an equivalent circuit model. Current and voltage are input online into the battery model. By recursive least square method the parameters are updated in real time. Moreover, when we use a recursive method to get real-time parameters, we add an extra proper factor to abandon old datum, which increases the real-time capability of state-of-power prediction. By assuming a constant current input and using the dynamic model we get the present dynamic voltage. Then by the second recursion, we derive the formula of 10-s resistance and calculate the SoP which can last for 10 seconds. The variables of the formula are the parameters which we get directly from the first recursion. Without using the parameters to calculate ohmic resistance, polarization resistance or capacitance of battery, it reduces much calculation amount and improves the calculation speed. This method is validated with datum from NEDC tests of Li-ion battery. The 10-s resistance values are predicted accurately. The method is suitable for the application in the battery management system of electric vehicles.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    On-line Lithium-Ion Battery State-of-Power Prediction by Twice Recursive Method Based on Dynamic Model


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Dai, Haifeng (Autor:in) / Wang, Xiaoyue (Autor:in) / Wei, Xuezhe (Autor:in)

    Kongress:

    WCX SAE World Congress Experience ; 2019



    Erscheinungsdatum :

    02.04.2019




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




    On-line Lithium-Ion Battery State-of-Power Prediction by Twice Recursive Method Based on Dynamic Model

    Wang, Xiaoyue / Dai, Haifeng / Wei, Xuezhe | British Library Conference Proceedings | 2019


    Lithium battery dynamic peak power prediction method

    PIAO CHANGHAO / YI MAOQING / WANG PINGZHONG et al. | Europäisches Patentamt | 2020

    Freier Zugriff

    Lithium ion battery energy state prediction method

    LI JUNJIE / ZHENG LI / MOU JIANHUI et al. | Europäisches Patentamt | 2024

    Freier Zugriff

    State estimation method for power lithium-ion battery based on dynamic equilibrium voltage

    Wang, Qiuting / Qi, Wei | British Library Online Contents | 2018


    Snowfield bicycle capable of positioning center line twice

    JIN ZHOUYUAN | Europäisches Patentamt | 2015

    Freier Zugriff