Technologies and techniques for processing a state of health for a battery in a battery management system. One or more data features may be extracted from a multivariate time series data associated with a plurality of vehicles, the multivariate time series data including battery information data for the vehicles. The one or more extracted data features are processed to represent the one or more extracted data features as a plurality of models comprising a series of outputs generated by one of several internal states. The processed extracted data features are clustered to group the data features into a plurality of first groups, based on a similarity metric. The plurality of first groups are then clustered to generate a second group, and a state of health indication may be determined for the battery information based on the second group.


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    Title :

    PROBABILISTIC MODELLING OF ELECTRIC VEHICLE CHARGING AND DRIVING USAGE BEHAVIOR WITH HIDDEN MARKOV MODEL-BASED CLUSTERING


    Contributors:

    Publication date :

    2024-07-04


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    B60L PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES , Antrieb von elektrisch angetriebenen Fahrzeugen / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung



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