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A Location-Aware Adaptive Vehicle Dynamics System (LAAVDS) is developed to assist the driver in maintaining vehicle handling capabilities through various driving maneuvers. An Intervention Strategy uses a novel measure of handling capability, the Performance Margin, to assess the need to intervene. The driver's commands are modulated to affect desired changes to the Performance Margin in a manner that is minimally intrusive to the driver's control authority. Real-time implementation requires the development of computationally efficient predictive vehicle models which is the focus of this work. This work develops one means to alter the future vehicle states: modulating the driver's throttle commands. First, changes to the longitudinal force are translated to changes in engine torque based on the current operating state (torque and speed) of the engine.

Ride control of military vehicles is challenging due to varied terrain and mission requirements such as operating weight. Achieving top speeds on rough terrain is typically considered a key performance parameter, which is always constrained by ride discomfort. Many military vehicles using passive suspensions suffer with compromised performance due to single tuning solution. To further stretch the performance domain to achieving higher speeds on rough roads, semi-active suspensions may offer a wide range of damping possibilities under varying conditions. In this paper, various semi-active control strategies are examined, and improvements have been made, particularly, to the acceleration-driven damper (ADD) strategy to make the approach more robust for varying operating conditions. A seven degrees of freedom ride model and a quarter-car model were developed that were excited by a random road process input modeled using an auto-regressive time series model.

This paper presents the extended Kalman filter-based sideslip angle estimator design using a nonlinear 5DoF single-track vehicle dynamics model with stochastic modeling of tire forces. Lumped front and rear tire forces have been modeled as first-order random walk state variables. The proposed estimator is primarily designed for vehicle sideslip angle estimation; however it can also be used for estimation of tire forces and cornering stiffness. This estimator design does not rely on linearization of the tire force characteristics, it is robust against the variations of the tire parameters, and does not require the information on coefficient of friction. The estimator performance has been first analyzed by means of computer simulations using the 10DoF two-track vehicle dynamics model and underlying magic formula tire model, and then experimentally validated by using data sets recorded on a test vehicle.

This study reanalyzes the data from a recent experimental report from the University of Utah investigating the effect on driving performance of auditory-vocal secondary tasks (such as cell phone and passenger conversations, speech-to-text, and a complex artificial cognitive task). The current objective is to estimate the relative risk of crashes associated with such auditory-vocal tasks. Contrary to the Utah study's assumption of an increase in crash risk from the attentional effects of cognitive load, a deeper analysis of the Utah data shows that driver self-regulation provides an effective countermeasure that offsets possible increases in crash risk. For example, drivers self-regulated their following distances to compensate for the slight increases in brake response time while performing auditory-vocal tasks. This new finding is supported by naturalistic driving data showing that cell phone conversation does not increase crash risk above that of normal baseline driving.

A key aim of research into cell phone tasks is to obtain an unbiased estimate of their relative risk (RR) for crashes. This paper re-examines five RR estimates of cell phone conversation in automobiles. The Toronto and Australian studies estimated an RR near 4, but used subjective estimates of driving and crash times. The OnStar, 100-Car, and a recent naturalistic study used objective measures of driving and crash times and estimated an RR near 1, not 4 - a major discrepancy. Analysis of data from GPS trip studies shows that people were in the car only 20% of the time on any given prior day at the same clock time they were in the car on a later day. Hence, the Toronto estimate of driving time during control windows must be reduced from 10 to 2 min.

Vehicle restraint system design is a difficult optimization problem to solve because (1) the nature of the problem is highly nonlinear, non-convex, noisy, and discontinuous; (2) there are large numbers of discrete and continuous design variables; (3) a design has to meet safety performance requirements for multiple crash modes simultaneously, hence there are a large number of design constraints. Based on the above knowledge of the problem, it is understandable why design of experiment (DOE) does not produce a high-percentage of feasible solutions, and it is difficult for response surface methods (RSM) to capture the true landscape of the problem. Furthermore, in order to keep the restraint system more robust, the complexity of restraint system content needs to be minimized in addition to minimizing the relative risk score to achieve New Car Assessment Program (NCAP) 5-star rating.

When a vehicle with a partially filled fuel tank undergoes sudden acceleration, braking, turning or pitching motion, fuel sloshing is experienced. It is important to establish a CAE methodology to accurately predict slosh phenomenon. Fuel slosh can lead to many failure modes such as noise, erroneous fuel indication, irregular fuel supply at low fuel level and durability issues caused by high impact forces on tank surface and internal parts. This paper summarizes activities carried out by the fuel system team at Ford Motor Company to develop and validate such CAE methodology. In particular two methods are discussed here. The first method is Volume Of Fluid (VOF) based incompressible multiphase Eulerian transient CAE method. The CFD solvers used here are Star CD and Star CCM+. The second method incorporates Fluid-Structure interaction (FSI) using Arbitrary Lagrangian-Eulerian (ALE) formulation.

Clutch wear is dominantly manifested as the reduction of friction plate thickness. For dry dual clutch with position-controlled electromechanical actuators this affects the accuracy of normal force control because of the increased clutch clearance. In order to compensate for the wear, dry dual clutch is equipped with wear compensation mechanism. The paper presents results of experimental characterization and mathematical modeling of two clutch wear related effects. The first one is the decrease of clutch friction plate thickness (i.e. increase of clutch clearance) which is described using friction material wear rate experimentally characterized using a pin-on-disc type tribometer test rig. The second wear related effect, namely the influence of the clutch wear compensation mechanism activation at various stages of clutch wear on main clutch characteristics, was experimentally characterized using a clutch test rig which incorporates entire clutch with related bell housing.

Pareto optimal map concept has been applied to the optimization of the vehicle system control (VSC) strategy for a power-split hybrid electric vehicle (HEV) system. The methodology relies on an inner-loop optimization process to define Pareto maps of the best engine and electric motor/generator operating points given wheel power demand, vehicle speed, and battery power. Selected levels of model fidelity, from simple to very detailed, can be used to generate the Pareto maps. Optimal control is achieved by applying Pontryagin's minimum principle which is based on minimization of the Hamiltonian comprised of the rate of fuel consumption and a co-state variable multiplied by the rate of change of battery SOC. The approach delivers optimal control for lowest fuel consumption over a drive cycle while accounting for all critical vehicle operating constraints, e.g. battery charge balance and power limits, and engine speed and torque limits.

In present paper, the process of joining aluminum alloy 6111T4 and steel HSLA340 sheets by self-piercing riveting (SPR) is studied. The rivet material properties were obtained by inverse modeling approach. Element erosion technique was adopted in the LS-DYNA/explicit analysis for the separation of upper sheet before the rivet penetrates into lower sheet. Maximum shear strain criterion was implemented for material failure after comparing several classic fracture criteria. LS-DYNA/implicit was used for springback analysis following the explicit riveting simulation. Large compressive residual stress was observed near frequent fatigue crack initiation sites, both around vicinity of middle inner wall of rivet shank and upper 6111T4 sheet.

Failure mode and fatigue behavior of dissimilar laser welds in lap-shear specimens of aluminum and copper sheets are investigated. Quasi-static tests and fatigue tests of laser-welded lap-shear specimens under different load ranges with the load ratio of 0.1 were conducted. Optical micrographs of the welds after the tests were examined to understand the failure modes of the specimens. For the specimens tested under quasi-static loading conditions, the micrograph indicates that the specimen failed through the fusion zone of the aluminum sheet. For the specimens tested under cyclic loading conditions, two types of failure modes were observed under different load ranges. One failure mode has a kinked crack initiating from the interfacial surface between the aluminum and copper sheets and growing into the aluminum fusion zone at an angle close to 90°.

The compressive behavior of lithium-iron phosphate battery cells is investigated by conducting in-plane constrained compression tests and out-of-plane compression tests of representative volume element (RVE) specimens. The results for cell RVE specimens under in-plane constrained compression tests without pre-strains and with pre-strains in the out-of-plane direction indicate that the load carrying capacity is characterized by the buckling of cell specimens. As the pre-strain increases, the nominal compressive stress-strain curve becomes higher. The nominal stress-strain curves in the out-of-plane direction were also obtained and used to determine the elastic moduli for the elastic buckling analyses of the cell components in the cell RVE specimens with different pre-strains. Based on the elastic buckling analyses for a beam with different lateral constraints due to different pre-strains in the out-of-plane direction, the number of half waves and the buckling stresses were obtained.

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.

Available methodologies for model bias identification are mainly regression-based approaches, such as Gaussian process, Bayesian inference-based models and so on. Accuracy and efficiency of these methodologies may degrade for characterizing the model bias when more system inputs are considered in the prediction model due to the curse of dimensionality for regression-based approaches. This paper proposes a copula-based approach for model bias identification without suffering the curse of dimensionality. The main idea is to build general statistical relationships between the model bias and the model prediction including all system inputs using copulas so that possible model bias distributions can be effectively identified at any new design configurations of the system. Two engineering case studies whose dimensionalities range from medium to high will be employed to demonstrate the effectiveness of the copula-based approach.

In vehicle design, response surface model (RSM) is commonly used as a surrogate of the high fidelity Finite Element (FE) model to reduce the computational time and improve the efficiency of design process. However, RSM introduces additional sources of uncertainty, such as model bias, which largely affect the reliability and robustness of the prediction results. The bias of RSM need to be addressed before the model is ready for extrapolation and design optimization. This paper further investigates the Bayesian inference based model extrapolation method which is previously proposed by the authors, and provides a systematic and integrated stochastic bias corrected model extrapolation and robustness design process under uncertainty. A real world vehicle design example is used to demonstrate the validity of the proposed method.

The objective of this paper focused on the modeling of an adaptive energy absorbing steering column which is the first phase of a study to develop a modeling methodology for an advanced steering wheel and column assembly. Early steering column designs often consisted of a simple long steel rod connecting the steering wheel to the steering gear box. In frontal collisions, a single-piece design steering column would often be displaced toward the driver as a result of front-end crush. Over time, engineers recognized the need to reduce the chance that a steering column would be displaced toward the driver in a frontal crash. As a result, collapsible, detachable, and other energy absorbing steering columns emerged as safer steering column designs. The safety-enhanced construction of the steering columns, whether collapsible, detachable, or other types, absorb rather than transfer frontal impact energy.

This paper presents the final phase of a study to develop the modeling methodology for an advanced steering assembly with a safety-enhanced steering wheel and an adaptive energy absorbing steering column. For passenger cars built before the 1960s, the steering column was designed to control vehicle direction with a simple rigid rod. In severe frontal crashes, this type of design would often be displaced rearward toward the driver due to front-end crush of the vehicle. Consequently, collapsible, detachable, and other energy absorbing steering columns emerged to address this type of kinematics. These safety-enhanced steering columns allow frontal impact energy to be absorbed by collapsing or breaking the steering columns, thus reducing the potential for rearward column movement in severe crashes. Recently, more advanced steering column designs have been developed that can adapt to different crash conditions including crash severity, occupant mass/size, seat position, and seatbelt usage.

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.

Active regeneration systems for cleaning diesel exhaust can operate at extremely high temperatures up to 1000°C. The extremely high temperatures create a unique challenge for the design of regeneration structural components near their melting temperatures. In this paper, the preparation of the sheet specimens and the test set-up based on induction heating for sheet specimens are first presented. Tensile test data at room temperature, 500, 700, 900 and 1100°C are then presented. The yield strength and tensile strength were observed to decrease with decreasing strain rate in tests conducted at 900 and 1100°C but no strain rate dependence was observed in the elastic properties for tests conducted below 900°C. The stress-life relations for under cyclic loading at 700 and 1100°C with and without hold time are then investigated. The fatigue test data show that the hold time at the maximum stress strongly affects the stress-life relation at high temperatures.

In this paper, the cyclic deformation behavior of an Al-Si-Cu alloy is studied under strain-controlled thermo-mechanical loading. Tests are carried out at temperatures from 20 °C to 440 °C. The effect of strain rate, hold time at temperature and loading sequence are investigated at each temperature. The results show that temperature has a significant effect on the cyclic deformation of Al-Si-Cu alloys. With increasing temperature, the effect of strain rate and hold time become more significant, while load sequence effects remain negligible within the investigated temperature range. Thus, an elasto-viscoplastic model is required for modeling the alloy's behavior at high temperature. This study provides an insight into the necessary information required for modeling of automotive engine components operating at elevated temperature.