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Safety and minimal transit time are vital during transportation of essential commodities and passengers, especially in winter conditions. Icy roads are the worst driving conditions with the least available friction, leaving valuable cargo and precious human lives at stake. The study investigates the available friction at the tire-ice interface due to changes in key operational parameters. Experimental analysis of tractive performance of tires on ice was carried out indoor, using the terramechanics rig located at the Advanced Vehicle Dynamics Laboratory (AVDL) at Virginia Tech. The friction-slip ratio curves obtained from indoor testing were inputted into TruckSIM, defining tire behavior for various ice scenarios and then simulating performance of trucks on ice. The shortcomings of simulations in considering the effects of all the operational parameters result in differences between findings of indoor testing and truck performance simulations.

Studying the kinetic and kinematics of the rim-tire combination is very important in full vehicle simulations, as well as for the tire design process. Tire maneuvers are either quasi-static, such as steady-state rolling, or dynamic, such as traction and braking. The rolling of the tire over obstacles and potholes and, more generally, over uneven roads are other examples of tire dynamic maneuvers. In the latter case, tire dynamic models are used for durability assessment of the vehicle chassis, and should be studied using high fidelity simulation models. In this study, a three-dimensional finite element model (FEM) has been developed using the commercial software package ABAQUS. The purpose of this study is to investigate the tire dynamic behavior in multiple case studies in which the transient characteristics are highly involved.

The brake architecture of hybrid and full electric vehicle includes the distinctive function of brake blending. Known approaches draw upon the maximum energy recuperation strategy and neglect the operation mode of friction brakes. Within this framework, an efficient control of the blending functions is demanded to compensate external disturbances induced by unpredictable variations of the pad disc friction coefficient. In addition, the control demand distribution between the conventional frictional brake system and the electric motors can incur failures that compromise the frictional braking performance and safety. However, deviation of friction coefficient value given in controller from actual one can induce undesirable deterioration of brake control functions.

To study vehicle dynamics, we need to know the forces and moments acting on the vehicle. The most important forces and moments acting on the vehicle are generated at the tire contact patch. A semi-empirical tire model was developed at Advanced Vehicle Dynamics Lab (AVDL) to use for vehicle simulations for steady-state conditions. In this paper, we extended that model to account for transient conditions. We present the basic concept, the development of the tire model, and selective simulation results. The transient tire model is developed by including the effects of the vertical load variations due to the velocity and the acceleration to the tire characteristic parameters. The simulation was performed for the semi-empirical transient tire model in two scenarios. The vehicle driving and braking maneuver was simulated to present the transient longitudinal tire behavior. The vehicle lane changing maneuver also was performed to present the transient lateral tire behavior.

Tire-pavement interaction noise (TPIN) is a dominant source for passenger cars and trucks above 40 km/h and 70 km/h, respectively. TPIN is mainly generated from the interaction between the tire and the pavement. In this paper, twenty-two passenger car radial (PCR) tires of the same size (16 in. radius) but with different tread patterns were tested on a non-porous asphalt pavement. For each tire, the noise data were collected using an on-board sound intensity (OBSI) system at five speeds in the range from 45 to 65 mph (from 72 to 105 km/h). The OBSI system used an optical sensor to record a once-per-revolution signal to monitor the vehicle speed. This signal was also used to perform order tracking analysis to break down the total tire noise into two components: tread pattern-related noise and non-tread pattern-related noise.

This paper is part of the European OWHEEL project. It proposes a method to improve the comfort of a vehicle by adaptively controlling the Camber and Toe angles of a rear suspension. The purpose is achieved through two actuators for each wheel, one that allows to change the Camber angle and the other the Toe angle. The control action is dynamically determined based on the error between the reference angle and the actual angles. The reference angles are not fixed over time but dynamically vary during the maneuver. The references vary with the aim of maintaining a Camber angle close to zero and a Toe angle that follows the trajectory of the vehicle during the curve. This improves the contact of the tire with the road. This solution allows the control system to be used flexibly for the different types of maneuvers that the vehicle could perform. An experimentally validated sports vehicle has been used to carry out the simulations. The original rear suspension is a Trailing-arm suspension.

An important problem of recent active safety applications is data acquisition for parameters of tire-road interaction, especially coefficient of friction or specific forces in contact patch. Analysis of present solutions in this field allows setting off the virtual and hardware-based determination of tire grip properties. The virtual procedures can be subclassified into Dynamics simulation method Statistical method Fuzzy logic method. The hardware-based procedures are connected with On-board sensors of direct tire grip measurement On-board sensors of indirect tire grip measurement Off-board (on-road) sensors. For above mentioned variants the appropriate engineering solutions are considered in the paper. The long-term approach in road identification centers on active safety applications with on-road sensors, which are integrated in intelligent transportation systems (ITS). The paper proposes conceptual structure for this system.

One of the principal goals of modern vehicle control systems is to ensure passenger safety during dangerous maneuvers. Their effectiveness relies on providing appropriate parameter inputs. Tire-road contact forces are among the most important because they provide helpful information that could be used to mitigate vehicle instabilities. Unfortunately, measuring these forces requires expensive instrumentation and is not suitable for commercial vehicles. Thus, accurately estimating them is a crucial task. In this work, two estimation approaches are compared, an observer method and a neural network learning technique. Both predict the lateral and longitudinal tire-road contact forces. The observer approach takes into account system nonlinearities and estimates the stochastic states by using an extended Kalman filter technique to perform data fusion based on the popular bicycle model.

Tire modeling plays an important role in the development of an Active Vehicle Safety System. As part of a larger project that aims at developing an integrated chassis control system, this study investigates the performance of a 19” all-season tire on ice for a sport utility vehicle. A design of experiment has been formulated to quantify the effect of operational parameters, specifically: wheel slip, normal load, and inflation pressure on the tire tractive performance. The experimental work was conducted on the Terramechanics Rig in the Advanced Vehicle Dynamics Laboratory at Virginia Tech. The paper investigates an approach for the parameterization of the Dugoff tire model based on the experimental data collected. Compared to other models, this model is attractive in terms of its simplicity, low number of parameters, and easy implementation for real-time applications.