This article describes the design and implementation of a fuzzy controller developed for improving car stability by controlling car side-slip angle. The strategy has been to estimate the slip angle by a trained neural network and to determine an appropriate force arrangement on the wheels to produce the necessary yaw moment to limit car side slip control. A seven degrees of freedom car model including nonlinear tire behavior is used in design stage. The results were then validated on a full car model in ADAMS having 156 DOF and including elements nonlinearities and flexibilities. The simulations show the capability of the designed controller in improving stability of the car in sever maneuvers.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Vehicle Stability Improvement Using Fuzzy Controller and Neural-Network Slip Angle Observer


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    International Body Engineering Conference & Exposition ; 2003



    Publication date :

    2003-10-27




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    20037164 2003-01-2883 Vehicle Stability Improvement Using Fuzzy Controller and Neural-Network Slip Angle Observer

    Durali, M. / Bahramzadeh, Y. / Society of Automotive Engineers of Japan | British Library Conference Proceedings | 2003


    VEHICLE BODY SIDE SLIP ANGLE OBSERVER

    Moldoveanu, F. / Cemat, M. / Georgescu, M. et al. | British Library Conference Proceedings | 2004



    Vehicle Body Slip Angle Estimation Using an Adaptive Observer

    Kaminaga, M. / Naito, G. / Society of Automotive Engineers of Japan | British Library Conference Proceedings | 1998


    Vehicle body slip angle estimaton using an adaptive observer

    Kaminaga, M. / Naito, G. | Tema Archive | 1998