To solve the problem that control system of the intelligent vehicle is hard to measure the vehicle mass and road gradient, this paper built a longitudinal dynamics model of vehicle. Based on theoretical model, discrete steady-state Kalman filter was used to estimate gradient of slope and vehicle mass, and simulation platform was established by Carsim and Maltab/Simulink to verify the accuracy and instantaneity of the algorithm. A proper acceleration sensor was selected, according to the stable Kalman filter theory. A real test was conducted, and the instantaneity and accuracy of this method for vehicle mass and road slope was verified by comparing with the data from inertial navigator.


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    Title :

    Estimation of vehicle mass and road slope based on steady-state Kalman filter


    Contributors:


    Publication date :

    2017-10-01


    Size :

    733424 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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