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We have recently obtained experimental data and used them to develop computational models to quantify occupant impact responses and injury risks for military vehicles during frontal crashes. The number of experimental tests and model runs are however, relatively small due to their high cost. While this is true across the auto industry, it is particularly critical for the Army and other government agencies operating under tight budget constraints. In this study we investigate through statistical simulations how the injury risk varies if a large number of experimental tests were conducted. We show that the injury risk distribution is skewed to the right implying that, although most physical tests result in a small injury risk, there are occasional physical tests for which the injury risk is extremely large. We compute the probabilities of such events and use them to identify optimum design conditions to minimize such probabilities.

Growing concerns about the environment, energy dependency, and unstable fuel prices have increased the market share of electric vehicles. This has led to an increased demand for energy efficient routing algorithms that are optimized for electric vehicles. Traditional routing algorithms are focused on finding the shortest distance or the least time route between two points. These approaches have been working well for fossil fueled vehicles. Electric vehicles, on the other hand, require different route optimization techniques. Negative edge costs, battery power and capacity limits, as well as vehicle parameters that are only available at query time, make the task of electric vehicle routing a challenging problem. In this paper, we present a simulated solution to the energy efficient routing for electric vehicles using Particle Swarm Optimization. Simulation results show improvements in the energy consumption of the electric vehicle when applied to a start-to-destination routing problem.

Frames are important structures found in many transportation applications such as automotive bodies and train cars. They are also widely employed in buildings, bridges, and other load bearing designs. When a frame is carrying multiple loads, it can potentially risk a catastrophic buckling failure. The loads on the frame may be non-proportional in that one force stays constant while the other is increased until buckling occurs. In this study the buckling problem is formulated as a constrained eigenvalue problem (CEVP). As opposed to other CEVP in which the eigenvectors are forced to comply with a number of the constraints, the eigenvalues in the current CEVP are subject to some equality constraints. A numerical algorithm for solving the constrained eigenvalue problem is presented. The algorithm is a simple trapping scheme in which the computation starts with an initial guess and a window containing the potential target for the eigenvalue is identified.

This paper discusses simplified lumped parameter thermal modeling of power train components. In particular, it discusses the tradeoff between model complexity and the ability to correlate the predicted temperatures and flow rates with measured data. The benefits and problems associated with using a three lumped mass model are explained and the value of this simpler model is promoted. The process for correlation and optimization using modern software tools is explained. Examples of models for engines and transmissions are illustrated along with their predictive abilities over typical driving cycles.

Spot Welding is an important welding technique which is widely used in automotive and aerospace industry. One of the keys of checking the quality of the welds is measuring the size of the nugget. In this paper, the Shearographic technique is utilized to test weld joint samples under the thermal loading condition. The goal is to identify the different group of the nuggets (i.e. small, middle, and large sizes, which indicate the quality of spot welds). In the experiments, the sample under test is fixed by a magnet method from behind at the four edges. Thermal loading was applied in the back side and the sample is inspected using the digital Shearographic system in the front side. Results show the great possibility of classifying the nugget size into three groups and the measurement is well repeatable.

Understanding reliability is critical in design, maintenance and durability analysis of engineering systems. A reliability simulation methodology is presented in this paper for vehicle fleets using limited data. The method can be used to estimate the reliability of non-repairable as well as repairable systems. It can optimally allocate, based on a target system reliability, individual component reliabilities using a multi-objective optimization algorithm. The algorithm establishes a Pareto front that can be used for optimal tradeoff between reliability and the associated cost. The method uses Monte Carlo simulation to estimate the system failure rate and reliability as a function of time. The probability density functions (PDF) of the time between failures for all components of the system are estimated using either limited data or a user-supplied MTBF (mean time between failures) and its coefficient of variation.

Shearography is an optical technique developed for full-field measurement of surface deformation. It has since been accepted by industry as a practical nondestructive testing technique for evaluating the structural integrity of components and structures. Qualitatively, shearography reveals flaws from flaw-induced, anomalous deformation in the component under inspection, and quantitatively, shearography assesses the detected flaws through back-calculation from the anomalous deformation. This paper demonstrates that, with the use of multiple-frequency acoustical excitation together with the time-integrated shearographic recording technique, rapid and automated assessment of the integrity of adhesive-bonded composite structures can be realized in the actual plant environment.

This paper discusses the feasibility and issues associated with integrating a consumer off-the shelf product into a vehicle. For this evaluation, we selected a handheld personal computer (HPC), cellular telephone and modem to integrate with the vehicle audio, climate and system controls. Connectivity between the HPC and the vehicle is established by the use of the standard infrared serial data link that comes with the HPC. Connectivity outside the vehicle uses a cellular telephone for voice and a cellular digital packet data (CDPD) modem for data. This system is built into the Dodge ESX-2 hybrid powered concept vehicle for demonstration.

The rapid growth of information technology has the potential to affect many of the reasons why people drive. The Internet is arguably the most significant recent milestone in the growth of information technology. This paper examines the ways Internet communication might affect the travel experience by a) eliminating traditional reasons for personal travel, b) providing new reasons, c) changing the balance between personal and freight travel, and d) changing trip length distribution. Changes of the types listed could affect the product demand "mix" for electric, hybrid-electric and fuel cell vehicles being developed.

This study analyzes the vibration characteristics of the valve train of a 2.0L SOHC Chrysler Corp. Neon engine over a range of operating speeds to investigate and demonstrate the advantages and limitations of various dynamic measurements such as displacement, velocity, and acceleration in this application. The valve train was tested in a motoring fixture at speeds of 500 to 3500 camshaft rpm. The advantages of analyzing both time and frequency domain measurements are described. Both frequency and order analysis were done on the data. The theoretical order spectra of cam displacement and acceleration were computed and compared to the experimental data. Deconvolution was used to uncover characteristic frequencies of vibration in the system. The theoretical cam acceleration spectrum was deconvolved from measured acceleration spectra to reveal the frequency response function of the follower system.

To understand how the passenger compartment cavity interacts with the surrounding panels (roof, windshield, dash panel, etc) a numerical panel contribution analysis was performed using FEA and BEA techniques. An experimental panel contribution analysis was conducted by Reiter Automotive Systems. Test results showed good correlation with the simulation results. After gaining some insight into panel contributions for power train noise, an attempt was made to introduce beads in panels to reduce vibration levels. A fully trimmed body structural-acoustic FEA model was used in this analysis. A network of massless beam elements was created in the model. This full structural-acoustic FEA model was then used to determine the optimal location for the beads, using the added beams as optimization variables.

Hand dismantling of certain automotive parts has been an accepted process to remove high value materials, but in large scale recycling this may not be economical. In plastics, a pure non contaminated material stream is critical for maintaining high material values and this means designing plastic parts that can be machine separated. One candidate for separating the plastics in vehicle subsystems such as instrument panels and door trim panels is density separation. In order to better understand what processes are required to develop design requirements for automated plastic separation methods Chrysler and the Vehicle Recycling Partnership have undertaken a major materials separation study with MBA Polymers. In this paper, we describe the material separation methods and the application of these methods to three automotive interior assemblies.

Environmental costs are a delayed financial burden that result from product decisions made early in the product life cycle--early material choices may create regulatory and waste management costs that were not factored into the acquisition cost. This paper outlines a step-wise approach to determine decision points; environmental, health, safety and recycling (EHS&R) cost drivers that affect decisions; and sources of information required to conduct a Life Cycle Management (LCM) review. Additionally, how LCM fits into the larger concurrent engineering framework is illustrated with an electrocoat primer example. Upstream and downstream supply chain processes are reviewed, as well as organizational challenges that affect the decision process.

Energy management materials are widely used in automotive interiors in instrument panel, knee bolster, and door absorber applications to reduce the risk of injury to an occupant during a crash. Automobile manufacturers must meet standards set by the National Highway Traffic Safety Administration (NHTSA) that identify maximum levels of injury to an occupant. The recent NHTSA upgrade to the Federal Motor Vehicle Safety Standard (FMVSS) 201 test procedure(1) for upper interior head impact protection has prompted energy management materials' use in several new areas of affected vehicles. While vehicle evaluations continue, results to date show that energy management foams can be effective in reducing the head injury criterion [HIC(d)] to acceptable government and OEM levels.

A few years ago, electric vehicles (EVs) were considered to be objects of the distant future … technology that was still in its infancy, not yet ready and for those outside the “high pollution” areas probably not even worth the expenditure. But the present day scenario has changed dramatically. In the United States of America, several states are following California's lead and the need for the operating fleets to commit to purchase of Zero Emission vehicles (ZEVs) is becoming a requirement. In order to make the technology available to the utilities … as well as the public, state of the art, affordable batteries are essential for making EVs a reality and an effective means of transportation.

Due to new regulations, emissions development and compliance testing have become more complex. The amount of data acquired, the number of test types, and the variety of test conditions have increased greatly. Due to this increase, managing test information from request to analysis of results has become a critical factor. Also, automated test result presentation and test storage increases the value and quality of each test. This paper describes a computer system developed to cope with the increasing complexity of vehicle emission testing.

Testing for vehicle emissions and fuel economy certification occurs primarily on chassis dynamometers in a laboratory setting and therefore the actual road conditions, such as forces due to tire rolling resistance and internal friction, must be simulated. Test track coastdown procedures measure vehicle road load forces and produce an equation which relates these forces to velocity. The recent inclusion of onboard anemometry has allowed the coastdown procedure to account for varying wind effects; however, the new anemometer based mechanical loss coefficients do not take into account ambient weather conditions. The two purposes of this study are (1) to determine the new tire rolling resistance temperature correction coefficient that should be used when test ambient temperature is different from the standard reference value of 68°F, and (2) to investigate the effects of auxiliary measurements, such as other ambient conditions and vehicle settings, on this correction coefficient.

The J1850 bus requirements promote an unique and well characterized physical layer behavior developed through the learning curve of previous multiplex solutions. Design requirements such as: 1) Reliably interconnecting all of the vehicle's most complex modules, 2) Consistently withstanding the vehicle's harsh environment, and 3) Meeting SAE's functionality requirements, were all a formidable task to achieve. This paper will highlight the path taken to achieve a J1850 Bus interface which successfully met all of the design and functional goals. Chrysler's C2D insights will be discussed and related to goals for J1850. Other design considerations will also be discussed such as EMC issues, custom test equipment, and vehicle and component testability. In turn, silicon processes with special structures and topologies will be discussed relating the specific design with the needed electrical behavior. The HIP7020 J1850 BUS TRANSCEIVER I/O for MULTIPLEX WIRING accomplishes these requirements.

MIL 3's OPNET simulator was used to model Chrysler's J1850 bus. Modeled were both J1850 bus characteristics and those portions of control modules (e.g., the engine controller) which communicate on the bus. Current Chrysler control module algorithms and proposed Chrysler J1850 message formats were used to design the control module models. The control module models include all messages which are transmitted at fixed intervals over the J1850 bus. The effects of function-based messages (e.g., messages to be transmitted on a particular sensor or push-button reading) on system load were investigated by transmitting an additional message with a fixed, relatively high priority at 50 millisecond intervals.

Vacuum insulation and phase-change thermal storage have been used to enhance the heat retention of a prototype catalytic converter. Storing heat in the converter between trips allows exhaust gases to be converted more quickly, significantly reducing cold-start emissions. Using a small metal hydride, the thermal conductance of the vacuum insulation can be varied continuously between 0.49 and 27 W/m2K (R-12 to R-0.2 insulation) to prevent overheating of the catalyst. A prototype was installed in a Dodge Neon with a 2.0-liter engine. Following a standard preconditioning and a 23-hour cold soak, an FTP (Federal Test Procedure) emissions test was performed. Although exhaust temperatures during the preconditioning were not hot enough to melt the phase-change material, the vacuum insulation performed well, resulting in a converter temperature of 146°C after the 23-hour cold soak at 27°C.