The research project 'Controllability of Road Vehicles at the Limits of Tyre Adhesion' (CROVLA) was established to investigate how tyre and chassis properties contribute to the handling characteristics and stability of vehicles operating at or near to the limit condition. The project involved the Department of Transport, SP Tyres UK Limited, Jaguar Cars and Cranfield University. An extensive proving ground test program of typical limit handling tests provided characteristic driver input and vehicle response data for a variety of vehicle configurations. The test data analysis was based on the concept of correlation. Cross- correlation coefficients and average response time delays were obtained for various pairs of quantities, namely steering angle and torque for the input and yaw rate and lateral acceleration for the response. The predictability of the vehicle response was evaluated by the rate by which the correlation coefficients change with severity. Analogous to the proving ground work, vehicle dynamics simulations were carried out. Two programs were employed to study the steady state performance and the transient limit handling behaviour. The 'Steady State Cornering Model' was used to confirm some basic suspension design rules established for optimising the lateral adhesion of a suspension design. The importance of controlling camber and vehicle jacking by an appropriate suspension design was identified. A detailed vehicle model was built-up using the simulation code AUTOSIM. After validating the model against proving ground data, some parametric studies were conducted to quantify the effects of suspension and tyre properties on the transient limit response behaviour. Proving ground and simulation results suggest that response time lags and cross- correlation coefficients in combination with other handling parameters can be used as objective quality measures. The results quantified to what extent tyre and chassis modifications change the limit handling behaviour.

A ground vehicle is a dynamic system containing many non-linear components, ranging from the non-linear engine response to the tyre-road interface. In pursuit of developing driver-assist systems for accident avoidance, as well as fully autonomous vehicles, the application of modern mechatronics systems to vehicles are widely investigated. Extensive work has been done in an attempt to model and control the lateral response of the vehicle system utilising a wide variety of conventional control and intelligent systems theory. The majority of driver models are however intended for low speed applications where the vehicle dynamics are fairly linear. This study proposes the use of adaptive control strategies as robust driver models capable of steering the vehicle without explicit knowledge of vehicle parameters. A Model Predictive Controller (MPC), self-tuning regulator and Linear Quadratic Self-Tuning Regulator (LQSTR) updated through the use of an Auto Regression with eXogenous input (ARX) model that describes the relation between the vehicle steering angle and yaw rate are considered as solutions. The strategies are evaluated by performing a double lane change in simulation using a validated full vehicle model in MSC ADAMS and comparing the maximum stable speed and lateral offset from the required path. It is found that all the adaptive controllers are able to successfully steer the vehicle through the manoeuvre with no prior knowledge of the vehicle parameters. An LQSTR proves to be the best adaptive strategy for driver model applications, delivering a stable response well into the non-linear tyre force regime. This controller is implemented on a fully instrumented Land Rover 110 of the Vehicle Dynamics Group at the University of Pretoria fitted with a semi-active spring-damper suspension that can be switched between two discrete setting representing opposite extremes of the desired response namely: ride mode (soft spring and low damping) and handling mode (stiff spring and high damping). The controller yields a stable response through a severe double lane change (DLC) up to the handling limit of the vehicle, safely completing the DLC at a maximum speed of 90 km/h all suspension configurations. The LQSTR also proves to be robust by following the same path for all suspension configurations through the manoeuvre for vehicle speeds up to 75 km/h. Validation is continued by successfully navigating the Gerotek dynamic handling track, as well as by performing a DLC manoeuvre on an off-road terrain. The study successfully developed and validated a driver model that is robust against variations in vehicle parameters and friction coefficients. / Dissertation (MEng)--University of Pretoria, 2015. / Mechanical and Aeronautical Engineering / Unrestricted