Search Results

To realistically predict the dynamics of a vehicle, the forces and moments in the contact patch must be accurately computed. A two-dimensional semi-empirical transient tire model was previously developed in the Advanced Vehicle Dynamics Lab (AVDL) at Virginia Tech, and extended the capabilities of the steady-state tire model also developed at AVDL. In this paper, a three-dimensional semi-empirical transient tire model is presented. The tire structure is modeled by an elastic ring supported on a spring and damper system. The elastic ring represents the belt ring and the spring and damper system represents the sidewall and the tread element. The analysis of the deformation of the tire structure with camber angle is performed on a flat surface to obtain the geometry of the contact patch and the normal pressure distribution. The forces and the moments are formulated using empirical data and based on theoretical mechanics.

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.

Mission demands for U.S. military tactical trucks require them to transport a broad array of cargo types, including intermodal containers. The wide range of mass properties associated with these diverse cargo requirements has resulted in potential for steering stability issues. The potential for steering stability issues largely originates from the high mobility characteristics of single-unit military tactical trucks relative to typical commercial cargo carriers. To quantify the influence of cargo variations on stability, vehicle dynamics experiments were conducted to obtain steering stability measurements for a tactical cargo truck hauling a broad range of rigid cargo loadings. The basic relationship for the understeer gradient measure of directional response behavior and observed data trends from the physical experiments were used to evaluate the relationship between the steering stability of the truck and the mass properties of the cargo.

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.

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.