Browsing by Subject "Slip Angle"

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    New sensors and estimation systems for the measurement of tire-road friction coefficient and tire slip variables.
    (2009-11) Erdogan, Gurkan
    This thesis introduces two new measurement systems developed for the estimation of tire-road friction coefficient and tire slip variables on highway vehicles. The first part of the thesis focuses on the development and experimental evaluation of a friction estimation system based on a novel adaptive feedforward vibration cancellation algorithm. The friction estimation utilizes a small instrumented wheel on the vehicle. Unlike other systems previously documented in literature, the developed system can provide a continuous measurement of the friction coefficient under all vehicle maneuvers, even when the longitudinal and lateral accelerations are both zero. A key challenge in the development of the estimation system is the need to remove the influence of vibrations and the influence of vehicle maneuvers from the measured signal of a force sensor. An adaptive feedforward algorithm based on the use of accelerometer signals as reference inputs is developed. The parameters of the feedforward model are estimated by the adaptive algorithm and serve to determine the value of the friction coefficient. The experimental performance of the adaptive feedforward algorithm is shown to be significantly superior to that of a simple cross-correlation based algorithm for friction estimation. The second part of the thesis introduces a simple approach for the analysis of tire deformations and proposes a new wireless piezoelectric tire sensor for the measurements of physically meaningful tire deformations. The tire deformation profile inside the contact patch can be used for the estimation of tire slip variables, tire forces and tire road friction coefficient. A wireless piezoelectric tire sensor for the specific case of slip angle and tire-road friction coefficient estimation is developed in this work. A sensor which decouples the lateral sidewall deformation from the radial and tangential sidewall deformations is designed. The slope of the lateral deflection profile at the leading edge of the contact patch is used to estimate the slip angle. A second order polynomial is used to model the lateral deflection profile of the sidewall. The parameters of this function are employed to estimate the lateral force and the conventional brush model is employed to estimate the tire road friction coefficient.
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    State, parameter, and unknown input estimation problems in active automotive safety applications.
    (2011-09) Phanomchoeng, Gridsada
    A variety of driver assistance systems such as traction control, electronic stability control (ESC), rollover prevention and lane departure avoidance systems are being developed by automotive manufacturers to reduce driver burden, partially automate normal driving operations, and reduce accidents. The effectiveness of these driver assistance systems can be significant enhanced if the real-time values of several vehicle parameters and state variables, namely tire-road friction coefficient, slip angle, roll angle, and rollover index, can be known. Since there are no inexpensive sensors available to measure these variables, it is necessary to estimate them. However, due to the significant nonlinear dynamics in a vehicle, due to unknown and changing plant parameters, and due to the presence of unknown input disturbances, the design of estimation algorithms for this application is challenging. This dissertation develops a new approach to observer design for nonlinear systems in which the nonlinearity has a globally (or locally) bounded Jacobian. The developed approach utilizes a modified version of the mean value theorem to express the nonlinearity in the estimation error dynamics as a convex combination of known matrices with time varying coefficients. The observer gains are then obtained by solving linear matrix inequalities (LMIs). A number of illustrative examples are presented to show that the developed approach is less conservative and more useful than the standard Lipschitz assumption based nonlinear observer. The developed nonlinear observer is utilized for estimation of slip angle, longitudinal vehicle velocity, and vehicle roll angle. In order to predict and prevent vehicle rollovers in tripped situations, it is necessary to estimate the vertical tire forces in the presence of unknown road disturbance inputs. An approach to estimate unknown disturbance inputs in nonlinear systems using dynamic model inversion and a modified version of the mean value theorem is presented. The developed theory is used to estimate vertical tire forces and predict tripped rollovers in situations involving road bumps, potholes, and lateral unknown force inputs. To estimate the tire-road friction coefficients at each individual tire of the vehicle, algorithms to estimate longitudinal forces and slip ratios at each tire are proposed. Subsequently, tire-road friction coefficients are obtained using recursive least squares parameter estimators that exploit the relationship between longitudinal force and slip ratio at each tire. The developed approaches are evaluated through simulations with industry standard software, CARSIM, with experimental tests on a Volvo XC90 sport utility vehicle and with experimental tests on a 1/8th scaled vehicle. The simulation and experimental results show that the developed approaches can reliably estimate the vehicle parameters and state variables needed for effective ESC and rollover prevention applications.