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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.

This paper describes a multi-degree-of-freedom model of a three-wheeled car implemented in Matlab®. The purpose was to investigate the dynamics of the car (assumed to be rigid on its suspension) during cornering. While the problems associated with three-wheeled cars are well known, much of the guidance in the literature and off-the-shelf software assumes a conventional four-wheeled car. Consequently, the authors were approached with a battery-electric concept car which was thought to offer better performance than the existing variants because the use of hub motors lowered the center of gravity and, hence, reduced rollover coefficient. However, simulation of the vehicle model in cornering shows that the concept is still prone to instability. Indeed, it suffers greater roll velocities than a comparable three-wheeled car with an internal combustion engine (ICE) because the ratio of sprung to unsprung mass is significantly altered.

This paper presents a driver assistance system designed to minimize the effect of driver reaction time on lane and speed maintenance operations. Nearly-instantaneous correcting actions are provided through a hierarchical arrangement of behaviors, by avoiding the time lag associated with deliberative or planning steps found in many control algorithms. Concepts originating in the field of robotics, including artificial potential fields and behavior-based systems, are interpreted for application to automotive control, where vehicle dynamics places considerable practical constraints on implementation. Ideas found in the study of emergent behavior in nature provide continuous, non-stepwise control signals, suitable for additive corrective inputs at highway velocities. This approach is effective for a substantial subset of road automobiles operating over a variety of speeds.

Semi-active suspension control deals principally with high bandwidth modulation of passively generated damper forces. When a properly designed semi-active damper is used in an otherwise conventional suspension there is much evidence that a superior overall system results. Large off-road vehicles, such as military transport vehicles, traveling at high speeds over rough terrain, possess suspension control requirements which are different from a road going vehicle. This paper develops these control requirements.

It is commonly accepted that the principal functions of an automobile suspension are to control low frequency rigid body motions, provide comfort to passengers, and to reduce tire normal force variation so that predictable handling is maintained. A good argument for reducing normal force variation is that in the extreme, if a tire is off the ground, it for certain cannot generate any lateral forces, and thus compromises lateral dynamics. The direct relationship between road holding and dynamic tire normal force variation is quantified sparsely in the literature. In this paper a relatively simple model is proposed which exposes how normal force variation at the front and rear directly affects the vehicle yaw rate and lateral acceleration. It is shown that normal force variation at the front has potentially the same effect on lateral dynamics as does the steering input.

Vehicle stability augmentation has been refined over many years, and currently there are commercial systems that control right/left braking and throttle to create vehicles that remain controlled when road conditions are very poor. These systems typically use yaw rate and lateral acceleration in their control philosophy. The tire/road friction coefficient, μ, has a significant role in vehicle longitudinal and lateral control, and there has been associated efforts to measure or estimate the road surface condition to provide additional information for the stability augmentation system. In this paper, a differential braking control strategy using yaw rate feedback, coupled with μ feedforward is introduced for a vehicle cornering on different μ roads. A nonlinear 4-wheel car model is developed. A desired yaw rate is calculated from the reference model based on the driver steering input.