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The purpose of this study is to determine the effect of tire operating conditions, such as the tire inflation pressure, speed, and load on the change of the first mode of vibration. A wide base FEA tire (445/50R22.5) is virtually tested on a 2.5m diameter circular drum with a 10mm cleat using PAM-Crash code. The varying parameters are altered separately and are as follows: inflation pressure, varying from 50 psi to 165 psi, rotational speed, changing from 20 km/h to 100 km/h, and the applied load will fluctuate from 1,500 lbs. to 9000 lbs. Through a comparison of previous literature, the PAM-Crash FFT algorithmic results have been validated.

Modern Finite Element Analysis (FEA) techniques allow for accurate simulation of various non-linear systems. However they are limited in their simulation of particulate matter. This research uses smooth particle hydrodynamics (SPH) in addition to FEA techniques to model the properties of soils, which allows for particle-level replication of soils. Selected soils are simulated in a virtual environment and validated using the pressure-sinkage and shear tests. A truck tire model is created based on standard heavy vehicle tires and validated using static deflection, contact footprint, and dynamic first mode of vibration tests. The validated tires and soils are used to create a virtual terrain and the tire is placed on the soil, loaded, and run over the soil at various speeds. The results of these simulations show that the SPH modeling technique offers higher accuracy than comparable FEA models for soft soils at a higher computational cost.

The rigid-ring tire model is a simplified tire model that describes a tire's behaviour under known conditions through various in-plane and out-of-plane parameters. The complex structure of the tire model is simplified into a spring-mass-damper system and can have its behaviour parameterized using principles of mechanical vibrations. By designing non-linear simulations of the tire model in specific situations, these parameters can be determined. They include, but are not limited to, the cornering stiffness, vertical damping constants, self-aligning torque stiffness and relaxation length. In addition, off-road parameters can be determined using similar methods to parameterize the tire model's behaviour in soft soils. By using Finite Element Analysis (FEA) modeling methods, validated soil models are introduced to the simulations to find additional soft soil parameters.

This paper will review several different emission control systems for heavy duty diesel (HDD) applications aimed at future legislations. The focus will be on the (DOC+CSF+SCR+ASC) configuration. As of today, various SCR technologies are used on commercial vehicles around the globe. Moving beyond EuroVI/US10 emission levels, both fuel consumption savings and higher catalyst system efficiency are required. Therefore, significant system optimization has to be considered. Examples of this include: catalyst development, optimized thermal management, advanced urea dosing calibrations, and optimized SCR inlet NO:NO2 ratios. The aim of this paper is to provide a thorough system screening using a range of advanced SCR technologies, where the pros and cons from a system perspective will be discussed. Further optimization of selected systems will also be reviewed. The results suggest that current legislation requirements can be met for all SCR catalysts under investigation.

This paper investigates the tire-road interaction for tires equipped with two different solid rubber material definitions within a Finite Element Analysis virtual environment, ESI PAMCRASH. A Mixed Service Drive truck tire sized 315/80R22.5 is designed with two different solid rubber material definitions: a legacy hyperelastic solid Mooney-Rivlin material definition and an Ogden hyperelastic solid material definition. The popular Mooney-Rivlin is a material definition for solid rubber simulation that is not built with element elimination and is not easily applicable to thermal applications. The Ogden hyperelastic material definition for rubber simulations allows for element destruction. Therefore, it is of interest and more suited for designing a tire model with wear and thermal capabilities.

Exhaust aftertreatment systems are essential components in modern powertrains, needed to reach the low legislated levels of NOx and soot emissions. A well designed diesel engine exhaust aftertreatment system can have NOx conversion rates above 95%. However, to achieve high conversion the aftertreatment system must be warm. Because of this, large parts of the total NOx emissions come from cold starts where the engine has been turned off long enough for the aftertreatment system to cool down and loose its capacity to reduce NOx. It is therefore important to understand how the aftertreatment cools down when the engine in turned off. Experimental data for a catalyst cool-down process is presented and analyzed. The analysis shows that it is important to capture the spatial distribution of temperatures both in axial and radial directions. The data and analysis are used to design a catalyst thermal model that can be used for model based catalyst temperature monitoring and control.

This paper focuses on predicting the rolling resistance and hydroplaning of a wide base truck tire (Size: 445/50R22.5) on dry and wet surfaces. The rolling resistance and hydroplaning are predicted at various inflation pressures, loads, velocities, and water depths. The wide base truck tire was previously modeled and validated using Finite Element Analysis (FEA) technique in virtual performance software (Pam-Crash). The water is modeled using Smoothed-Particle Hydrodynamics (SPH) method and Murnaghan equation of state. A water layer is first built on top of an FEA rigid surface to represent a wet surface. The truck tire is then inflated to the desired pressure. A vertical load is then applied to the center of the tire. For rolling resistance tests variable constant longitudinal speeds are applied to the center of the tire. The forces in the vertical and longitudinal directions are computed, and the rolling resistance is calculated.