In recent years, vehicle fire accidents have become the main obstacle to the large-scale popularization of the application of new energy vehicles, and most of the accidents are closely related to power batteries. This paper proposes a thermal runaway warning method for lithium-ion power batteries based on the theory of entropy. Firstly, data pre-processing by sliding window and dividing interval is used to improve the calculation efficiency and diagnosis accuracy, and the indicator of warning coefficient which can quantify the risk is proposed based on the calculation result of information entropy, the analysis and verification results of actual vehicles show that the method based on information entropy can realize the early warning of thermal runaway vehicles. Secondly, the singular spectrum analysis is applied to the thermal runaway detection to reflect the risk possibility of each cell. By calculating the singular spectrum entropy value of the cells in the thermal runaway vehicle, the fast location of the faulty cells can be achieved, and this method can provide a clear target for vehicle maintenance and monitoring the battery pack status. Finally, the two algorithms are combined and validated in a dataset from actual vehicles to propose a framework capable of monitoring and warning in the cloud-based battery management platform.


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    Titel :

    Research on Battery Fault Diagnosis Method Based on Entropy


    Beteiligte:
    Zhang, Zhengjie (Autor:in) / Wang, Mingyue (Autor:in) / Jin, Yuntao (Autor:in) / Sun, Yefan (Autor:in) / Liu, Xinhua (Autor:in) / Wang, Rui (Autor:in) / Yang, Shichun (Autor:in)


    Erscheinungsdatum :

    24.09.2023


    Format / Umfang :

    734036 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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