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One of the issues in stamping of advanced high strength steels (AHSS) is the stretch bending fracture on a sharp radius (commonly referred to as shear fracture). Shear fracture typically occurs at a strain level below the conventional forming limit curve (FLC). Therefore it is difficult to predict in computer simulations using the FLC as the failure criterion. A modified Mohr-Coulomb (M-C) fracture criterion has been developed to predict shear fracture. The model parameters for several AHSS have been calibrated using various tests including the butter-fly shaped shear test. In this paper, validation simulations are conducted using the modified (M-C) fracture criterion for a dual phase (DP) 780 steel to predict fracture in the stretch forming simulator (SFS) test and the bending under tension (BUT) test. Various deformation fracture modes are analyzed, and the range of usability of the criterion is identified.

Fillet and plug weld are commonly used in structural applications in commercial heavy vehicles. This paper is primarily concerned with an investigation of the full field deformations fields in fillet and plug welds using three dimensional digital image correlation (3D-DIC). Two identical vehicle parts are constructed using a fillet weld for one specimen, and a plug weld for the other. The specimens are loaded under quasi-static conditions with simultaneous measurement of load, displacements and strain gage measurements. Strain gage locations are selected based on the results of a finite element analysis model. 3D-DIC measurements are constructed using a two camera setup. Thus, 3D-DIC measurements are compared to strain gage measurements and finite element predictions. The effectiveness of the non-contact full field method is evaluated for application to studying the weld details considered and potential for fatigue damage and durability.

Flexible polyurethane foam is the main cushioning element used in car seats. Optimization of an occupied seat's static and dynamic behavior requires models of foam that are accurate over a wide range of excitation and pre-compression conditions. In this research, a method is described to estimate the parameters of a global model of the foam behavior from data gathered in a series of impulse tests at different settling points. The estimated model is capable of describing the responses gathered from all the impulse tests using a unique set of parameters. The global model structure includes a nonlinear elastic term and a hereditary viscoelastic term. The model can be used to predict the settling point for each mass used and, by expanding the model about that settling point, local linear models of the response to impulsive excitation can be derived. From this analysis the relationship between the local linear model parameters and the global model parameters is defined.

As the piston pin works under significant mechanical load, it is susceptible to wear, seizure, and structural failure, especially in heavy duty internal combustion engines. It has been found that the friction loss associated with the pin is comparable to that of the piston, and can be reduced when the interface geometry is properly modified. However, the mechanism that leads to such friction reduction, as well as the approaches towards further improvement, remain unknown. This work develops a piston pin lubrication model capable of simulating the interaction between the pin, the piston, and the connecting rod. The model integrates dynamics, solid contact, oil transport, and lubrication theory, and applies an efficient numerical scheme with second order accuracy to solve the highly stiff equations. As a first approach, the current model assumes every component to be rigid.

In this study, the formation and decomposition of ammonium nitrate (AN) on a state-of-the-art extruded vanadium-based SCR catalyst (V-SCR) under simulated exhaust conditions has been evaluated. Results show that AN readily forms and accumulates at temperatures below 200°C when exposed to NH3 and NO2. The rate of AN accumulation increases with decreasing temperature. A new low temperature NH3 release peak (not present following NH3 storage conditions with NH3 only) becomes apparent after AN accumulation at 100 and 125°C. This new NH3 release, with a peak release temperature of approximately 180°C, is evaluated in detail to better determine its origin. BET surface area, and thermal gravimetric analysis/differential scanning calorimetry (TGA/DSC), and reactor-based experiments are all used to characterize AN formed on the V-SCR catalyst in comparison to pure AN.

One field-returned DPF loaded with a high amount of ash is examined using experimental and modeling approaches. The ash-related design factors are collected by coupling the inspection results from terahertz spectroscopy with a calibrated DPF model. The obtained ash packing density, ash layer permeability and ash distribution profile are then used in the simulation to assess the ash impact on DPF backpressure and regeneration behaviors. The following features have been observed during the simulation: 1 The ash packing density, ash layer permeability and ash distribution profile should be collected at the same time to ensure the accurate prediction of ash impact on DPF backpressure. Missing one ash property could mislead the measurement of the other two parameters and thus affects the DPF backpressure estimation. 2 The ash buildup would gradually increase the frequency for the backpressure-based active soot regeneration.

In this article, a new method for achieving piano black appearance is discussed. Using a technique called Direct Coating, developed by Covestro, components have been produced with a smooth, high-gloss surface, which demonstrates improved scratch resistance and the ability to recover from minor scratches. For this development project, the Hyundai Santa Fe exterior door trim was selected due to the simple geometry and severe performance requirements. This allowed for optimization of molding conditions and comparison of the performance to the current production part. The prototype part demonstrated improved surface quality compared to paint, and passed car wash, chemical, and weathering test specifications. In addition to addressing quality issues, this method offers cost savings by eliminating the traditional painting process, which is expensive due to long cycle time, multi-step processing, and emissions regulations.

This article is concerned with identification of true stress-strain curve under biaxial tension of thermoplastic polymers. A new type of biaxial tension attachment was embedded first in a universal material test machine, which is able to transform unidirectional loading of the test machine to biaxial loading on the specimen with constant velocity. Cruciform specimen geometry was optimized via FE modeling. Three methods of calculating true stress in biaxial tension tests were compared, based on incompressibility assumption, linear elastic theory and inverse engineering method, respectively. The inverse engineering method is more appropriate for thermoplastic polymers since it considers the practical volume change of the material during biaxial tension deformation. The strategy of data processing was established to obtain biaxial tension true stress-strain curves of different thermoplastic polymers.

The increasing use of diesel and gasoline particulate filters requires advanced on-board diagnostics (OBD) to prevent and detect filter failures and malfunctions. Early detection of upstream (engine-out) malfunctions is paramount to preventing irreversible damage to downstream aftertreatment system components. Such early detection can mitigate the failure of the particulate filter resulting in the escape of emissions exceeding permissible limits and extend the component life. However, despite best efforts at early detection and filter failure prevention, the OBD system must also be able to detect filter failures when they occur. In this study, radio frequency (RF) sensors were used to directly monitor the particulate filter state of health for both gasoline particulate filter (GPF) and diesel particulate filter (DPF) applications.

Connected and Autonomous Vehicles (CAV) rely on information obtained from sensors and communication to make decisions. In a Cooperative Vehicle Safety (CVS) system, information from remote vehicles (RV) is available at the host vehicle (HV) through the wireless network. Safety applications such as crash warning algorithms use this information to estimate the RV and HV states. However, this information is uncertain and sparse due to communication losses, limitations of communication protocols in high congestion scenarios, and perception errors caused by sensor limitations. In this paper we present a novel approach to improve the robustness of the CVS systems, by proposing an architecture that divide application and information/perception subsystems and a novel prediction method based on non-parametric Bayesian inference to mitigate the detrimental effect of data loss on the performance of safety applications.

The optimal control of anode H2 concentration in fuel cell is the key performance parameter for efficiency and durability of the fuel cell electric vehicle. Implementation of H2 concentration sensor in fuel processing system is the best option to achieve the optimal control operation, but the vulnerability of the chip in H2 concentration sensor to the moisture has not been overcome and no H2 concentration sensor for vehicle application is present in the world so far. Due to the immaturity of the H2 concentration sensor, a number of researches have been being made to keep the H2 concentration in the anode at certain level without H2 concentration sensors. However the effectiveness of those technologies has not been good to meet the design specification in all the operating range of the various driving cycles and environmental condition.

This paper discusses a technology for reducing the gas flow noise generated from the noise of the vehicle, especially the exhaust system. The primary function of the heat protector is thermal shutdown. However, due to the increase in engine power, downsizing of engines, and the rise of consumer's eye level, solutions about noise are now emphasized. To meet these needs, a new concept of heat protector manufacturing technology is required. A key component of this technology is the manufacturing technology of three-ply composite board which can absorb sound from the existing sound insulation aluminum heat protector. For this purpose, mold technology for punching aluminum sheet, optimization technique for punching effect, specific pattern design for high-strength/high-forming, sound absorbing material selection and composite sheet molding technology, and noise vibration reduction mounting technology for plate joining were developed.

Commercially available Third Generation Advanced High Strength Steels (GEN3 AHSS) are qualified by automakers worldwide. With an excellent combination of strength and ductility, GEN3 AHSS are cold-formable and have shown potential to replace press hardenable steels (PHS) in structural applications. With overall formability equivalent to 590DP, U. S. Steel 980 GEN3 AHSS (980 XG3™ AHSS) may achieve cold-formed component geometries similar to those achieved by hot-formed PHS. Furthermore 980 GEN3 AHSS demonstrates a substantial increase in post-forming yield strength due to the combined effects of work-hardening and bake-hardening-thereby contributing strongly toward crash energy management performance. The technical challenges and attributes of cold-formed 980 GEN3 AHSS are explored in this paper for an automotive rear rail application (currently PHS), including: formability analysis, wrinkling elimination and springback compensation.

Studies have shown that there are a significant number of chemical species present in engine exhaust particulate matter emissions. Additionally, the majority of current world-wide regulatory methods for measuring engine particulate emissions are gravimetrically based. As modern engines considerably reduce particulate mass emissions, these methods become less stable and begin to display higher levels of measurement uncertainty. In this study, a characterization of mass emissions from three heavy-duty diesel engines, with a range of particulate emission levels, was made in order to gain a better understanding of the variability and uncertainty associated with common mass measurement methods, as well as how well these methods compare with each other. Two gravimetric mass measurement methods and a reconstructed mass method were analyzed as part of the present study.

Diesel particulate filters are designed to reduce the mass emissions of diesel particulate matter and have been proven to be effective in this respect. Not much is known, however, about their effects on other unregulated chemical species. This study utilized source dilution sampling techniques to evaluate the effects of a catalyzed diesel particulate filter on a wide spectrum of chemical emissions from a heavy-duty diesel engine. The species analyzed included both criteria and unregulated compounds such as particulate matter (PM), carbon monoxide (CO), hydrocarbons (HC), inorganic ions, trace metallic compounds, elemental and organic carbon (EC and OC), polycyclic aromatic hydrocarbons (PAHs), and other organic compounds. Results showed a significant reduction for the emissions of PM mass, CO, HC, metals, EC, OC, and PAHs.

In today's highly competitive automotive markets manufacturers must provide high quality products to survive. Manufacturers can achieve higher levels of quality by changing or improving their manufacturing process and/or by product inspection where many strategies with different cost implications are often available. Cost of Quality (CoQ) reconciles the competing objectives of quality maximization and cost minimization and serves as a useful framework for comparing available manufacturing process and inspection alternatives. In this paper, an analytic CoQ framework is discussed and some key findings are demonstrated using a set of basic inspection strategy scenarios. A case of a welded automotive assembly is chosen to explore the CoQ tradeoffs in inspection strategy selection and the value of welding process improvement. In the assembly process, many individual components are welded in series and each weld is inspected for quality.

In order to understand better the operation of spark-ignition engines during the warm-up period, a computer model had been developed which simulates the thermal processes of the engine. This model is based on lumped thermal capacitance methods for the major engine components, as well as the exhaust system. Coolant and oil flows, and their respective heat transfer rates are modeled, as well as friction heat generation relations. Piston-liner heat transfer is calculated based on a thermal resistance method, which includes the effects of piston and ring material and design, oil film thickness, and piston-liner crevice. Piston/liner crevice changes are calculated based on thermal expansion rates and are used in conjunction with a crevice-region unburned hydrocarbon model to predict the contribution to emissions from this source.

A brake is a mechanical device that inhibits the motion by absorbing energy from a moving system. It is used for slowing or stopping a moving vehicle, wheel, axle, or to prevent its motion, most often accomplished by friction energy. Commonly, most brakes use friction between two surfaces pressed together to convert the kinetic energy of the moving object into heat, though other methods of energy conversion may be employed. If braking is repeated or sustained in high load or high-speed conditions, the motion will be unstable and can lead to a loss of stopping power because the disc capability for braking is not enough. These phenomena are generally defined as brake fading. Brake fade is caused by an overheating brake system. This paper describes the thermal modeling and process to predict the disk temperature under a condition which causes the fade characteristics.

This study was conducted to develop and validate a multidimensional measure of shift quality as perceived by drivers during kick-down shift events for automatic transmission vehicles. As part of the first study, a survey was conducted among common drivers to identify primary factors used to describe subjective gear-shifting qualities. A factor analysis on the survey data revealed four semantic subdimensions. These subdimensions include responsiveness, smoothness, unperceivable, and strength. Based on the four descriptive terms, a measure with semantic scales on each subdimension was developed and used in an experiment as the second study. Twelve participants drove and evaluated five vehicles with different gear shifting patterns. Participants were asked to make kick-down events with two different driving intentions (mild vs. sporty) across three different speeds on actual roadway (local streets and highway).

With the on- and off-road diesel engine emission regulations getting more stringent across the world, diesel aftertreatment systems are expected to deliver outstanding performance and reliability. These objectives should be met by fulfilling tight packaging constraints and incurring only modest material and testing costs. A major strategy for meeting these often conflicting requirements is the effective use of simulation tools such as computational fluid dynamics (CFD) in system design and performance evaluation. Prerequisites for using this CFD analysis-led-design approach, however, are knowledge of the confidence level of the predictions and knowledge of the appropriate transfer functions that establish the relationships between the measured performance parameters and model predictions. The primary aim of the present work is to develop statistically and physically relevant measures that assess the uniformity of flow in aftertreatment systems.