This article discusses algorithms to estimate parameters and states of articulated heavy vehicles. First, 3- and 5-degrees-of-freedom linear vehicle models of a tractor semitrailer are presented. Vehicle parameter estimation methods based on the dual extended Kalman filter and state estimation based on the Kalman filter are presented. A program of experimental tests on an instrumental heavy goods vehicle is described. Simulation and experimental results showed that the algorithms generate accurate estimates of vehicle parameters and states under most circumstances.


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    Title :

    Parameter and state estimation for articulated heavy vehicles


    Contributors:

    Published in:

    Vehicle System Dynamics ; 49 , 1-2 ; 399-418


    Publication date :

    2011-02-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




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