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The use of electric motors to independently control the torque of two or four wheels of a vehicle has the potential to significantly improve safety and handling. One virtue of electric motors is that their output torque can be accurately estimated. Using this known output torque, longitudinal tire force and coefficient of friction can be estimated via a controller output observer. This observer works by constructing a model of wheel dynamics, with longitudinal tire force as an unknown input quantity. A known wheel torque is input to the physical and modeled system and the resulting measured and predicted wheel speeds are compared. The error between the measured and predicted wheel speed is driven towards zero by a robust feedback controller. This controller modulates an estimate of longitudinal tire force used as an input by the wheel dynamics model. The resulting estimate of longitudinal tire force quickly converges towards the actual value with minimal computational expense.

A new control strategy for wheel slip control, considering the complete dynamics of the electro-hydraulic brake (EHB) system, is developed and experimentally validated in Cranfield University's HiL system. The control system is based on closed loop shaping Youla-parameterization method. The plant model is linearized about the nominal operating point, a Youla parameter is defined for all stabilizing feedback controller and control performance is achieved by employing closed loop shaping technique. The stability and performance of the controller are investigated in frequency and time domain, and verified by experiments using real EHB smart actuator fitted into the HiL system with driver in the loop.

Human expert drivers have the unique ability to combine correlated sensory inputs with repetitive learning to build complex perceptive models of the vehicle dynamics as well as certain key aspects of the tire-ground interface. This ability offers significant advantages for navigating a vehicle through the spatial and temporal uncertainties in a given environment. Conventional traction control algorithms utilize measurements of wheel slip to help insure that the wheels do not enter into an excessive slip condition such as burnout. This approach sacrifices peak performance to ensure that the slip limits are generic enough suck that burnout is avoided on a variety of surfaces: dry pavement, wet pavement, snow, gravel, etc. In this paper, a novel approach to traction control is developed using an anthropomimetic control synthesis strategy.

The incorporation of reliability theory into a fatigue analysis algorithm is studied. This probabilistic approach gives designers the ability to quantify “real world” variations existing in the material properties, geometry, and loading of engineering components. Such information would serve to enhance the speed and accuracy of current design techniques. An automobile wheel assembly is then introduced as an example of the applications of this durability/reliability design package.

A vehicle's response is predominately defined by the tire characteristics as they constitute the only contact between the vehicle and the road; and the surface friction condition is the primary attribute that determines these characteristics. The friction coefficient is not directly measurable through any sensor attachments in production-line vehicles. Therefore, current chassis control systems make use of various estimation methods to approximate a value. However a significant challenge is that these schemes require a certain level of perturbation (i.e. excitation by means of braking or traction) from the initial conditions to converge to the expected values; which might not be the case all the time during a regular drive.

The vertical force generated from terrain-tire interaction has long been of interest for vehicle dynamic simulations and chassis development. To improve simulation efficiency while still providing reliable load prediction, a terrain pre-filtering technique using a constraint mode tire model is developed. The wheel is assumed to convey one quarter of the vehicle load constantly. At each location along the tire's path, the wheel center height is adjusted until the spindle load reaches the pre-designated load. The resultant vertical trajectory of the wheel center can be used as an equivalent terrain profile input to a simplified tire model. During iterative simulations, the filtered terrain profile, coupled with a simple point follower tire model is used to predict the spindle force. The same vehicle dynamic simulation system coupled with constraint mode tire model is built to generate reference forces.