Accurate real-time information of wheel slip angle is essential for various active stability control systems. A number of techniques have been proposed to enhance quality of GPS based estimation. This paper exhibits a novel cost-effective strategy of individual wheel slip angle estimation for a rear-wheel-drive (RWD) vehicle. At any slip condition, the slip angle can be estimated using only measurement of steering angle, front wheel speeds, yaw rate, longitudinal and lateral accelerations, without requiring GPS data. On the basis of zero longitudinal slip at both front tires, the closed-form solutions for direct computation of wheel slip angles were derived via kinematic analysis of a planar four-wheel vehicle, and then primarily verified by computational simulation with prescribed functions of radius of curvature, vehicle speed, sideslip and steering angle. Neither integration nor tire friction model is required for this estimation methodology. In terms of implementation, a 1:10th scaled RWD vehicle was modified so that the steering angle, the front wheel rolling speeds, the vehicle yaw rate and the linear accelerations can be measured. Preliminary experiment was done on extremely random sideslip maneuvers beneath the global positioning using four recording cameras. By comparing with the vision-based reference, the individual wheel slip angles could be well estimated despite extreme tire slip. Other vehicle state variables- radius of curvature, vehicle sideslip and speed - may also be directly obtained from the kinematic relations. This proposed estimation methodology could then be alternatively applied for the full range slip angle estimation in advanced active safety systems.


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    Titel :

    Kinematics-Based Analytical Solution for Wheel Slip Angle Estimation of a RWD Vehicle with Drift


    Beteiligte:

    Erscheinungsdatum :

    2016-05-18


    Anmerkungen:

    Engineering Journal; Vol 20 No 2 (2016): Regular Issue; 89-107 ; 0125-8281



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629




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