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The pulleys employed in automotive accessory drive systems very often consist of a two piece assembly; a multitude of fastening techniques are used in completing the assembly. There are numerous assembly methods and a variety of distinct pulley configurations dictated by the various automobile manufacturers in accordance with individual accessory drive needs. An expert system is being developed to evaluate the merit of multiple assembly alternatives for a specific pulley application. The expert system provides a consistent evaluation tool for assembly alternatives, balancing the influence of product cost, strength and quality considerations. The knowledge-based system is implemented in an expert system shell called AGNESS (A Generalized Network-based Expert System Shell). The expert system judges the acceptability of various pulley assembly techniques, assigning a high “merit value” to the better designs and proportionately lower values to less desirable designs.

The addition of synthetic traffic to a driving simulation greatly enhances the realism of the virtual world. Giving this traffic human-like behavior is likewise desirable, and has been the focus of some research over the past few years. This paper presents a modular architecture for including autonomous traffic in a driving simulation, and describes the first steps taken toward the application of this architecture to the DaimlerChrysler Auburn Hills Simulator. By separating the planning part of the agent from the low-level control and vehicle dynamics systems, the described architecture permits the inclusion of powerful, previously developed components in a straightforward way; in the present application, agents use Soar to reason about their actions. This paper gives an overview of the structures of the agents, and of the entire system, describes the components and their implementations, and discusses the current state of the project and plans for the future.

A series of inflator tank tests was carried out to determine the amount of transient heat losses to the tank wall during these tests. The time history data of tank wall temperature, and tank interior gas temperature and pressure, were measured. The tank wall temperature data were analyzed using an inverse heat conduction method to generate the transient heat loss fluxes from the tank gas to the tank wall. The validity of the results are discussed along with the physical reasoning and experimental observations. This is the first part of an effort in a research project to develop a comprehensive heat transfer model to predict the transient heat losses to the tank wall during the inflator tank test.

Industrial tasks performed by standing workers are among those most commonly simulated using digital human models. Workers often walk, turn, and take acyclic steps as they perform these tasks. Current h uman modeling tools lack the capability to simulate these whole body motions accurately. Most models simulate walking by replaying joint angle trajectories corresponding to a general gait pattern. Turning is simulated poorly if at all, and violations of kinematic constraints between the feet and ground are common. Moreover, current models do not accurately predict foot placement with respect to loads and other hand targets, diminishing the utility of the associated ergonomic analyses. A new approach to simulating stepping and walking in task-oriented activities is proposed. Foot placements and motions are predicted from operator and task characteristics using empirical models derived from laboratory data and validated using field data from an auto assembly plant.

The rapid development of connected and automated vehicle technologies together with cloud-based mobility services are revolutionizing the transportation industry. As a result, huge amounts of data are being generated, collected, and utilized, hence providing tremendous business opportunities. However, this big data poses serious challenges mainly in terms of data privacy. The risks of privacy leakage are amplified by the information sharing nature of emerging mobility services and the recent advances in data analytics. In this paper, we provide an overview of the connected vehicle landscape and point out potential privacy threats. We demonstrate two of the risks, namely additional individual information inference and user de-anonymization, through concrete attack designs. We also propose corresponding countermeasures to defend against such privacy attacks. We evaluate the feasibility of such attacks and our defense strategies using real world vehicular data.

The need for improved understanding of new magnesium alloys for the automotive industry continues to grow as the application for these lightweight alloys expands to more demanding environments, particularly in drivetrain components. Their use at elevated temperatures, such as in transmission cases, presents a challenge because magnesium alloys generally have lower creep resistance than aluminum alloys currently employed for such applications. In this study, a new die cast magnesium alloy, MEZ, containing rare earth (RE) elements and zinc as principal alloying constituents, was examined for its bolt-load retention (BLR) properties. Preloads varied from 14 to 28 kN and test temperatures ranged from 125 to 175°C. At all test temperatures and preloads, MEZ retained the greatest fraction of the initial imposed preload when compared to the magnesium alloys AZ91D, AE42, AM50, and the AM50+Ca series alloys.

This paper presents an extension of our previous work on decomposition-based assembly synthesis [1], where the 3D finite element model of a vehicle body-in-white (BIW) is optimally decomposed into a set of components considering the stiffness of the assembled structure under given loading conditions, and the manufacturability and assemblability of each component. The stiffness of the assembled structure is evaluated by finite element analyses, where spot-welded joints are modeled as linear torsional springs. In order to allow close examinations of the trade-off among stiffness, manufacturability, and assemblability, the optimal decomposition problem is solved by multi-objective genetic algorithm [2,3], with graph-based crossover [4,5], combined with FEM analyses, generating Pareto optimal solutions. Two software programs are developed to implement the proposed method.

Despite remarkable progress made over the past 30 years, automobiles continue to be a major source of hydrocarbon emissions. The objective of this study is to evaluate whether variable exhaust valve opening (EVO) and exhaust valve closing (EVC) can be used to reduce hydrocarbon emissions. An automotive gasoline engine was tested with different EVO and EVC timings under steady-state and start-up conditions. The first strategy that was evaluated uses early EVO with standard EVC. Although exhaust gas temperature is increased and catalyst light-off time is reduced, the rapid drop in cylinder temperature increases cylinder-out hydrocarbons to such a degree that a net increase in hydrocarbon emissions results. The second strategy that was evaluated uses early EVO with early EVC. Early EVO reduces catalyst light-off time by increasing exhaust gas temperature and early EVC keeps the hydrocarbon-rich exhaust gas from the piston crevice from leaving the cylinder.

Driving simulators offer a safe alternative to on-road driving for the evaluation of performance. In addition, simulated drives allow for controlled manipulations of traffic situations producing a more consistent and objective assessment experience and outcome measure of crash risk. Yet, few simulator protocols have been validated for their ability to assess driving performance under conditions that result in actual collisions. This paper presents results from a new Simulated Driving Assessment (SDA), a 35- to-40-minute simulated assessment delivered on a Real-Time® simulator. The SDA was developed to represent typical scenarios in which teens crash, based on analyses from the National Motor Vehicle Crash Causation Survey (NMVCCS). A new metric, failure to brake, was calculated for the 7 potential rear-end scenarios included in the SDA and examined according two constructs: experience and skill.

A failure prediction methodology that can predict sheet metal failure under arbitrary deformation histories including rotating principal stretch directions and bending/unbending with consideration of damage evolution is reviewed in this paper. An anisotropic Gurson yield criterion is adopted to characterize the effects of microvoids on the load carrying capacity of sheet metals where Hill’s quadratic anisotropic yield criterion is used to describe the matrix normal anisotropy and planar isotropy. The evolution of the void damage is based on the growth, nucleation and coalescence of microvoids. Mroz’s anisotropic hardening rule, which was proposed based on the cyclic plastic behavior of metals observed in experiments, is generalized to characterize the anisotropic hardening behavior due to loading/unloading with consideration of the evolution of void volume fraction. The effects of yield surface curvature are also included in the plasticity model.

A comprehensive model for sprays emerging from high-pressure swirl injectors in DISI engines has been developed accounting for both primary and secondary atomization. The model considers the transient behavior of the pre-spray and the steady-state behavior of the main spray. The pre-spray modeling is based on an empirical solid cone approach with varying cone angle. The main spray modeling is based on the Liquid Instability Sheet Atomization (LISA) approach, which is extended here to include the effects of swirl. Mie Scattering, LIF, PIV and Laser Droplet Size Analyzer techniques have been used to produce a set of experimental data for model validation. Both qualitative comparisons of the evolution of the spray structure, as well as quantitative comparisons of spray tip penetration and droplet sizes have been made. It is concluded that the model compares favorably with data under atmospheric conditions.

There is a strong evidence that the overrepresentation of teen drivers in motor vehicle crashes is mainly due to their poor hazard perception skills, i.e., they are unskilled at appropriately detecting and responding to roadway hazards. This study evaluates two cuing systems designed to help teens better understand their driving environment. Both systems use directional color-coding to represent different levels of proximity between one’s vehicle and outside agents. The first system provides an overview of the location of adjacent objects in a head-up display in front of the driver and relies on drivers’ focal vision (focal cuing system). The second system presents similar information, but in the drivers’ peripheral vision, by using ambient lights (peripheral cuing system). Both systems were retrofitted into a test vehicle (2014 Toyota Camry). A within-subject experiment was conducted at the University of Michigan Mcity test-track facility.

This paper examines truck driver injury and loss of life in truck crashes related to cab crashworthiness. The paper provides analysis of truck driver fatality and injury in crashes to provide a better understanding of how injury occurs and industry initiatives focused on reducing the number of truck occupant fatalities and the severity of injuries. The commercial vehicle focus is on truck-tractors and single unit trucks in the Class 7 and 8 weight range. The analysis used UMTRI's Trucks Involved in Fatal Accidents (TIFA) survey file and NHTSA's General Estimates System (GES) file for categorical analysis and the Large Truck Crash Causation Study (LTCCS) for a supplemental clinical review of cab performance in frontal and rollover crash types. The paper includes analysis of crashes producing truck driver fatalities or injuries, a review of regulatory development and industry safety initiatives including barriers to implementation.

At the forefront of intelligent vehicle technologies are vehicle-to-vehicle communication (V2V) and vehicle-infrastructure integration (VII). Their capabilities can be added to currently-available systems, such as adaptive cruise control (ACC), to drastically decrease the number and severity of collisions, to ease traffic flow, and to consequently improve fuel efficiency and environmental friendliness. There has been extensive government, industry, and academic involvement in developing these technologies. This paper explores the capabilities and challenges of vehicle-based technology and examines ways that policymakers can foster implementation at the federal, state, and local levels.

The influence of the bulk in-cylinder flow on the spray evolution, evaporation, fuel-air mixing and subsequent flame propagation has been studied in an optical SIDI engine. Quantitative LIF imaging of equivalence ratios was used to characterize the mixture formation and the influence of the local equivalence ratio at the time of spark on the flame propagation. Two extreme bulk flow conditions - high and low swirl - were investigated and pronounced differences in mixture homogeneity and flame propagation were found and characterized.

A primary goal of large eddy simulation, LES, is to capture in-cylinder cycle-to-cycle variability, CCV. This is a first step to assess the efficacy of 35 consecutive computed motored cycles to capture the kinetic energy in the TCC-III engine. This includes both the intra-cycle production and dissipation as well as the kinetic energy CCV. The approach is to sample and compare the simulated three-dimensional velocity equivalently to the available two-component two-dimensional PIV velocity measurements. The volume-averaged scale-resolved kinetic energy from the LES is sampled in three slabs, which are volumes equal to the two axial and one azimuthal PIV fields-of-view and laser sheet thickness. Prior to the comparison, the effects of sampling a cutting plane versus a slab and slabs of different thicknesses are assessed. The effects of sampling only two components and three discrete planar regions is assessed.

Based on a review of existing theoretical and empirical knowledge of the mechanics of pneumatic tires and tire/vehicle systems, a requirement is defined for experimental data relating the shear forces developed at the tire-road interface to the kinematic variables of influence. Test equipment to satisfy this requirement consists of two complementary pieces of apparatus: a laboratory facility which is a modified version of the B. F. Goodrich flat-bed tester, and a mobile device which consists of a three-component (Fx, Fy, Mz) strain-gage dynamometer mounted on a heavy duty highway tractor. The latter provides a capability for testing at speeds up to 70 mph, normal loads up to 2000 lb, tire sideslip angles up to 18 deg, and steady state or programmed variations in longitudinal tire slip from fully locked (100% slip) to 30% overdriven (-30% slip). Representative samples of tire mechanics data obtained using the new equipment are presented and discussed.

In order to develop confidence in numerical models which are used for automotive crash simulations, results are compared with test data. Modeling assumptions are made when constructing a simulation model for a complex system, such as a vehicle. Through a thorough understanding of the modeling assumptions an appropriate set of variables can be selected and adjusted in order to improve correlation with test data. Such a process can lead to better modeling practices when constructing a simulation model. Comparisons between the time history of acceleration responses from test and simulations are the most challenging. Computing accelerations correctly is more difficult compared to computing displacements, velocities, or intrusion levels due to the second order differentiation with time. In this paper a methodology for enabling the update of a simulation model for improved correlation is presented.

Since muscles act to translate an electrical impulse from the central nervous system into motion, it is essential to have a suitable mathematical model for muscles and groups of muscles for a virtual soldier environment. This paper presents a methodology in which the muscle contraction is broken down into three distinct physiological processes: calcium release and re-absorption by the sarcoplasmic reticulum, the rate at which calcium binds and unbinds to troponin, and the generation of force due to cross-bridge cycling and the elasticity of the muscle fibers. These processes have been successfully modeled by Ding and Wexler as a system of coupled differential and algebraic equations. These equations give the calcium-time history and the force time history of the muscle. By varying the electrical stimulation rates, the muscles can produce forces of varying magnitude and duration over which the force can be maintained.

Using the CDC (SAE J224), a comparison of the NASS data and the UMTRI field accident files (UM series) indicates a similar distribution of offset frontal crashes. Offset frontal damage occurs in 56-61% of crashes, often involving more than one third of the front of the car. Lap-shoulder belted drivers sustain more AIS 2 or greater injuries when there is interior intrusion and occur more often when the offset damage is in front of the driver. However, this may well be due to the severity of the crash. European studies have no uniformity as to offset frontal collision descriptors are difficult to interpret, or to compare one to another.