Search Results

Most ground vehicles related accidents occur when the friction demand to perform a maneuver with a certain vehicle and tires exceeds the coefficient of friction of the pavement surface. As generally known, the forces and moments acting on the vehicle body are mainly generated at the tire-road surface interface. The common characteristics of tire forces on any surface include a linear region where the forces vary linearly with respect to the relative slip values; and a nonlinear region where the forces saturate and may even start decreasing. The experience of most of the daily drivers on the roads is limited within this linear region where the dynamic behavior of the vehicle remains proportional to the driver’s inputs. Therefore, an unexpected change in tire or surface characteristics (due to a change in surface friction, large driver inputs, etc.) may easily cause the driver to panic and/or to lose his/her ability to maintain a stable vehicle.

This paper presents a brake control strategy with a novel approach to the allocation of actuator effort in an electric vehicle. The proposed strategy relies on a combination of the conventional hydraulic braking system and the electric machine in order to improve braking performance. The higher response frequency of the electric machine is paired with the additional braking torque employed by the hydraulic brakes using an integrated control allocation strategy, which allows for a constant availability of a faster and more accurate modulation of both wheel torque and wheel speed. Therefore, the availability of an electric machine as a fast longitudinal actuator yields to an improved tracking of the desired wheel slip, especially when compared to the hydraulic actuators used in traditional braking applications.

Research of the past century has demonstrated that wheel camber regulation provides great potential to improve vehicle safety and performance. This led to the development of various prototypes of the camber mechanisms over the last decade. An overview of the existing prototypes is discussed in the presented paper. Most of the investigations related to camber control cover open-loop maneuvers to evaluate a vehicle response. However, a driver’s perception and his reaction can be the most critical factor during vehicle operation. Therefore, the research goal of the presented study is to assess an influence of active camber control on steering feel and driving performance using a driving simulator. In the proposed investigation, a dSPACE ASM vehicle model has been extended by introducing advanced models of steering system and active camber regulation. The steering system describes dynamics of steering components (upper and lower columns, torsion bar, steering rack and others).

The road profile has been shown to have significant effects on various vehicle conditions including ride, handling, fatigue or even energy efficiency; as a result it has become a variable of interest in the design and control of numerous vehicle parts. In this study, an integrated state estimation algorithm is proposed that can provide continuous information on road elevation and profile variations, primarily to be used in active suspension controls. A novel tire instrumentation technology (smart tire) is adopted together with a sensor couple of wheel attached accelerometer and suspension deflection sensor as observer inputs. The algorithm utilizes an adaptive Kalman filter (AKF) structure that provides the sprung and unsprung mass displacements to a sliding-mode differentiator, which then yields to the estimation of road elevations and the corresponding road profile along with the quarter car states.

The increasing demand of energy use in transportation systems combined with the limited supply of fossil hydrocarbons to support conventional engines has led to a strong resurgence in interest for electric vehicles (EVs). Although EVs offer the possibility of decoupling the issue of energy source from the primary torque generator in an automobile, the current technology is yet to match the well-developed internal combustion (IC) systems, especially in terms of energy capacity and travel range. In this study, the influence of rolling-resistance on the energy efficiency and road holding of electric vehicles is investigated. Rolling resistance is taken in the context of energy loss (e.g. the mechanical energy converted into other sources of energy) for a unit distance traveled by the tire.

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 effectiveness of active vehicle safety systems soars with the advances in on-board electronics that allows increasingly complex algorithms to be implemented. Numerous studies expose statistical results that underline the rate of reduction in the involvement of the vehicles equipped with such systems in road accidents. These facts clearly indicate how much the current systems have advanced. Nevertheless there are several areas of improvement for these systems, among which utilizing more information about tire-road states (e.g., tire forces, tire slip and slip-angle, surface friction) ranks very high due to the key role tires play in providing directional stability and control. This study introduces the use of an arriving technology, namely the smart tire technology, to estimate and utilize the aforementioned tire-road states along with an optimal tire force allocation scheme for improved vehicle stability.

In the case of modern day vehicle control systems employing a feedback control structure, a real-time estimate of the tire-road contact parameters is invaluable for enhancing the performance of the chassis control systems such as anti-lock braking systems (ABS) and electronic stability control (ESC) systems. However, at present, the commercially available tire monitoring systems are not equipped to sense and transmit high speed dynamic variables used for real-time active safety control systems. Consequently, under the circumstances of sudden changes to the road conditions, the driver's ability to maintain control of the vehicle maybe at risk. In many cases, this requires intervention from the chassis control systems onboard the vehicle. Although these systems perform well in a variety of situations, their performance can be improved if a real-time estimate of the tire-road friction coefficient is available.

Active safety systems have become an essential part of today's vehicles including SUVs and LTVs. Although they have advanced in many aspects, there are still many areas that they can be improved. Especially being able to obtain information about tire-vehicle states (e.g. tire slip-ratio, tire slip-angle, tire forces, tire-road friction coefficient), would be significant due to the key role tires play in providing directional stability and control. This paper first presents the implementation strategy for a dynamic tire slip-angle estimation methodology using a combination of a tire based sensor and an observer system. The observer utilizes two schemes, first of which employs a Sliding Mode Observer to obtain lateral and longitudinal tire forces. The second step then utilizes the force information and outputs the tire slip-angle using a Luenberger observer and linearized tire model equations.