This paper will describe the development of a load estimation algorithm that is used to estimate the load parameters necessary to detect a vehicle’s proximity to rollover. When operating a vehicle near its handling limits or with large loads, vehicle rollover must be considered for safe operation. Vehicle mass and center of gravity (CG) height play a large role in a vehicle’s rollover propensity. Cargo and passenger vehicles operate under a range of load configurations; therefore, changes in load should be estimated. Researchers have often developed load estimation and rollover detection algorithms separately. This paper will develop a load estimation algorithm and use the load estimates and vehicle states to detect rollover. The load estimation algorithm uses total least squares and is broken into two parts. First, mass is estimated based on a “full-car” dynamic ride model. Next, the CG height and inertia are estimated using the previously estimated mass and a dynamic roll model. Least squares is a popular method for load estimation. Least Squares (LS) assumes that there is no measurement noise which is violated in this application. Total Least Squares (TLS) accounts for measurement noise and provides more accurate estimates when measurement noise is present. Simulated data from CarSim is used to produce sensor measurements. Inertial measurement unit (IMU) and suspension defection sensors are used to measure the appropriate vehicle states. Noise is added to each measurement. Accuracy of the load estimation will be discussed and compared to the least squares approach. Rollover detection using load estimates will be analyzed and compared to rollover detection that does not account for changes in load.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Vehicle Load Estimation Using Recursive Total Least Squares for Rollover Detection


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Bevly, David M. (Autor:in) / Hilyer, Trenton (Autor:in)

    Kongress:

    WCX SAE World Congress Experience ; 2022



    Erscheinungsdatum :

    2022-03-29




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




    Vehicle Load Estimation Using Recursive Total Least Squares for Rollover Detection

    Hilyer, Trenton / Bevly, David M. | British Library Conference Proceedings | 2022


    Vehicle Load Estimation Using Recursive Total Least Squares for Rollover Detection

    Hilyer, Trenton / Bevly, David M. | British Library Conference Proceedings | 2022



    ONLINE ESTIMATION OF VEHICLE DRIVING RESISTANCE PARAMETERS WITH RECURSIVE LEAST SQUARES AND RECURSIVE TOTAL LEAST SQUARES

    Rhode, S. / Gauterin, F. / Institute of Electrical and Electronics Engineers | British Library Conference Proceedings | 2013