As more and more electric vehicles emerge in our daily operation progressively, a very critical challenge lies in the prediction of remaining driving-time distance (for cars) or flying time-distance (for aircraft). This information is important, particularly in the case of unmanned vehicles, because such vehicles can become self-aware, autonomously compute its own capabilities, and identify how to best plan and successfully complete vehicular missions safely. In case of electric aircrafts, computing remaining flying time is also safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle.


    Access

    Access via TIB

    Check availability in my library


    Export, share and cite



    Title :

    Prognostics and Health Monitoring: Application to Electric Vehicles


    Contributors:

    Publication date :

    2019


    Size :

    34 pages


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English