The accuracy estimation of the peak power can guarantee the battery’s safety, and make full use of the battery performance during the allowed safe range, thus improving the safety, power and quick charge performance. Up to now, the peak power in the electric vehicles is usually acquired by the peak power, SOC and temperature map, thus requiring a lot of offline experiments, and not taking the real-time polarization into account. Besides, the map method is strongly influenced by the accuracy of SOC and battery aging. In response to these circumstances, this paper has developed a model-based method for peak power online estimation. Firstly, the one order resistance-capacity equivalent circuit model has been employed to model the battery; Secondly, the parameters of the model have been on-line estimated by the particle swarm optimization (PSO) method; Thirdly, through the model-based method, the peak power of the battery has been obtained; Finally, a simplified version of the federal urban driving schedule (SFUDS) with inserted pulse experiment has been conducted to verify the peak power estimated. The result indicates that the proposed method is accurate and reliable with the 25 W maximum absolute error of the peak power.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Model-Based Peak Power Estimation of Lithium-Ion Batteries for Electric Vehicles


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Shun, Xiang (Autor:in) / Ying, Zheng (Autor:in) / Munan, Hong (Autor:in) / Qian, Zhu (Autor:in) / Yazhou, Guo (Autor:in) / Bo, Liu (Autor:in) / Bo, Yang (Autor:in)


    Erscheinungsdatum :

    2020-11-05


    Format / Umfang :

    12 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Model-Based Peak Power Estimation of Lithium-Ion Batteries for Electric Vehicles

    Shun, Xiang / Ying, Zheng / Munan, Hong et al. | TIBKAT | 2021



    Advanced Lithium-Ion Batteries for Electric Vehicles

    Brohm, T. / Maul, M. / Meissner, E. | British Library Conference Proceedings | 1998


    Lithium-iron sulfide batteries for electric vehicles

    Nelson, P.A. / Chilenskas, A.A. / Steunenberg, R.K. | Tema Archiv | 1978