The connection of a vehicle to the cloud in combination with machine learning algorithms offers new approaches to vehicle health management. New insights are gained not only by monitoring an individual vehicle but also by comparing the meta-data of an individual vehicle with those of the entire fleet. A benefit of these insights is better prediction of the remaining useful life of a chassis component, which enables preventative maintenance and in turn increases the vehicle owner’s perception of enhanced vehicle dependability. This is particularly important in the context of automated vehicle fleets, which are expected to have a much higher usage rate than privately owned cars. Further benefits include reduction of warranty and cloud-based root-cause analysis.

    The paper covers the underlying concepts of vehicle health management, including the “digital twin,” and describes a steering use-case, as well as Integrated Vehicle Health Management standardization frameworks.


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    Title :

    New Approaches to Vehicle Health Management via a Digital Twin


    Additional title:

    Proceedings


    Contributors:


    Publication date :

    2022-04-19


    Size :

    18 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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