A systematic method to identify the kinematic point positions (x-, y- and z-values) of a rear axle has been developed with help of Kinematics and Compliance (KnC) measurements from the Suspension Motion Simulator (SMS) at TU Dresden. The kinematic points were at first measured with a ROMER arm, which is a coordinate measurement machine (CMM). The KnC simulation results of a MBS (Multibody System) model in ADAMS/Car based on CMM data were verified by KnC measurements from the SMS test rig. To reduce the calculation time, the total identification process was defined in two steps, rough and fine identification. In the first step of rough identification, the boundary conditions were constant lengths of links or constant distances between two kinematic points as to find possible spatial positions of kinematic points in a restricted range. For fine identification, the objective function considered also the KnC characteristic curve error between MBS simulations and test rig measurements, which was realized by a simulation exchange between ADAMS/Car and MATLAB. The errors between identified positions of kinematic points and CMM data were in an acceptable range, which has validated the developed identification method.


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    Titel :

    Identification of Kinematic Points Based on KnC Measurements from the Suspension Motion Simulator


    Weitere Titelangaben:

    Lect.Notes Mechanical Engineering


    Beteiligte:
    Klomp, Matthijs (Herausgeber:in) / Bruzelius, Fredrik (Herausgeber:in) / Nielsen, Jens (Herausgeber:in) / Hillemyr, Angela (Herausgeber:in) / Liu, Chao (Autor:in) / Zhang, Yi (Autor:in) / Deubel, Clemens (Autor:in) / Kocksch, Felix (Autor:in) / Kubenz, Jan (Autor:in) / Prokop, Günther (Autor:in)

    Kongress:

    The IAVSD International Symposium on Dynamics of Vehicles on Roads and Tracks ; 2019 ; Gothenburg, Sweden August 12, 2019 - August 16, 2019



    Erscheinungsdatum :

    2020-02-13


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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