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ERRATUM: In the article Reference 24 should read as follows: 24. Han, T., Booth, A., Song, S., Styles, D., and Hoard, J., “Review and A Conceptual Model of Exhaust Gas Recirculation (EGR) Cooler Fouling Deposition and Removal Mechanism” Proceedings of the Int. Conf. on Heat Exchanger Fouling and Cleaning, 2015”

Because niobium-clad 304L stainless steel sheets are considered for use as bipolar plates in polymer electrolyte membrane (PEM) fuel cells, their mechanical behavior and failure mechanism are important to be examined. As-rolled and annealed specimens were tested in tension, bending and flattening. The effects of annealing temperature and time on the mechanical behavior and failure mechanism were investigated. Micrographic analyses of bent and flattened specimens showed that the as-rolled specimens have limited ductility and that the annealed specimens can develop an intermetallic layer of thickness of a few microns. The annealed specimens failed due to the breakage of intermetallic layer causing localized necking and the subsequent failure of Nb layer. The springback angles of the as-rolled and annealed specimens were also obtained from guided-bend tests.

In 2006, there were approximately 23,500 rear-end crashes involving heavy trucks (i.e., gross vehicle weight greater than 4,536 kg). The Enhanced Rear Signaling (ERS) for Heavy Trucks project was developed by the Federal Motor Carrier Safety Administration (FMCSA) to investigate methods to reduce or mitigate those crashes where a heavy truck has been struck from behind by another vehicle. Visual warnings have been shown to be effective, assuming the following driver is looking directly at the warning display or has his/her eyes drawn to it. A visual warning can be placed where it is needed and it can be designed so that its meaning is nearly unambiguous. FMCSA contracted with the Virginia Tech Transportation Institute (VTTI) to investigate potential benefit of additional rear warning-light configurations as rear-end crash countermeasures for heavy trucks.

Biodiesel has been widely accepted as an alternative for fossil-derived diesel fuel for use in compression ignition (CI) engines. Poor oxidative stability and cold flow properties restrict the use of biodiesel beyond current B20 blend levels (20% biodiesel in 80% ULSD) for vehicle applications. Maintaining the properties of B20 as specified by ASTM D7476-08 is important because, once out of spec, B20 may cause injector coke formation, fuel filter plugging, increased exhaust emissions, and overall loss of engine performance. While the properties of fresh B20 may be within the specifications, under engine operating and longer storage conditions B20 could deteriorate. In a diesel engine, the fuel that goes to the injector and does not enter the cylinder is recycled back to the fuel tank. The re-circulated fuel returns to the fuel tank at an elevate temperature, which can cause thermal oxidation.

The use of butanol as an alternative biofuel blend component for conventional diesel fuel has been under extensive investigation. However, some fuel properties such as cetane number and lubricity fall below the accepted values as described by the ASTM D 975 diesel specifications. Blending 10% butanol with #2 ULSD decreases the cetane number by 7% (from 41.6 to 39.0). At higher butanol blend levels, i.e., 20% v/v, the cetane number decrease cannot be compensated for; even with the addition of a 2000 ppm level commercial cetane improver. The decreased cetane number, or in other words, increased ignition delay, can be attributed to the increased blend level of low cetane butanol as well as the critical physical properties for better atomization of fuels during auto ignition such as viscosity. The kinematic viscosity dropped sharply with increasing butanol blend level up to 25 % v/v, then increased with further increase of butanol blend level.

Under the borderline autoignition conditions experienced during cold-starting of diesel engines, the amount and composition of residual gases may play a deterministic role. Among the intermediate species produced by misfiring and partially firing cycles, formaldehyde (HCHO) is produced in significant enough amounts and is sufficiently stable to persist through the exhaust and intake strokes to kinetically affect autoignition of the following engine cycle. In this work, the effect of HCHO addition at various phases of autoignition of n-heptane-air mixtures is kinetically modeled. Results show that HCHO has a retarding effect on the earliest low-temperature heat release (LTHR) phase, largely by competition for hydroxyl (OH) radicals which inhibits fuel decomposition. Conversely, post-LTHR, the presence of HCHO accelerates the occurrence of high-temperature ignition.

Driver distraction is a topic of considerable interest, with the public debate centering on the use of cell phones and texting while driving. However, the driver distraction/overload issue is really much larger. It concerns specific tasks such as entering destinations on navigation systems, retrieving songs on MP3 players, accessing web pages, checking stocks, editing spreadsheets, and performing other tasks on smart phones, as well as, more generally, using in-vehicle information systems. Five major problems related to distraction/overload research and engineering and their solutions are addressed in this paper.

Fuel wall impingement commonly occurs in small-bore diesel engines. Particularly during engine starting, when wall temperatures are low, the evaporation rate of fuel film remaining from previous cycles plays a significant role in the autoignition process that is not fully understood. Pre-injection chemiluminescence (PIC), resulting from low-temperature oxidation of evaporating fuel film and residual gases, was measured over 3200 μsec intervals at the end of the compression strokes, but prior to fuel injection during a series of starting sequences in an optical diesel engine. These experiments were conducted to determine the effect of this parameter on combustion phasing and were conducted at initial engine temperatures of 30, 40, 50 and 60°C, at swirl ratios of 2.0 and 4.5 at 1000 RPM. PIC was determined to increase and be highly correlated with combustion phasing during initial cycles of the starting sequence.

This paper proposes a framework to perform design optimization of a series PHEV and investigates the impact of using real-world driving inputs on final design. Real-World driving is characterized from a database of naturalistic driving generated in Field Operational Tests. The procedure utilizes Markov chains to generate synthetic drive cycles representative of real-world driving. Subsequently, PHEV optimization is performed in two steps. First the optimal battery and motor sizes to most efficiently achieve a desired All Electric Range (AER) are determined. A synthetic cycle representative of driving over a given range is used for function evaluations. Then, the optimal engine size is obtained by considering fuel economy in the charge sustaining (CS) mode. The higher power/energy demands of real-world cycles lead to PHEV designs with substantially larger batteries and engines than those developed using repetitions of the federal urban cycle (UDDS).

With the increasing demand for fuel efficient vehicles, technologies like superplastic forming (SPF) are being developed and implemented to allow for the utilization of lightweight automotive sheet materials. While forming under superplastic conditions leads to increased formability in lightweight alloys, such as aluminum, the slower forming times required by the technology can limit the technology to low to mid production levels. One problem that can increase forming time is the reduction of forming pressure due to pressurizing (forming) gas leaks, during the forming cycle, at the die/sheet/blankholder interface. Traditionally, such leaks have been successfully addressed through the use of a seal bead. However, for advanced die technologies that result in reduced cycle times (such as hot draw mechanical performing, which combine aspects of mechanical preforming of the sheet metal followed by SPF), the use of seal beads can restrict the drawing of sheet material into the forming die.

This paper introduces a Hydraulic Linear Engine (HLE) concept and describes a model to simulate instantaneous engine behavior. The United States Environmental Protection Agency has developed an HLE prototype as an evolution of their previous six-cylinder, four-stroke, free-piston engine (FPE) hardware. The HLE design extracts work hydraulically, in a fashion identical to the initial FPE, and is intended for use in a series hydraulic hybrid vehicle. Unlike the FPE, however, the HLE utilizes a crank for improved timing control and increased robustness. Preliminary experimental results show significant speed fluctuations and cylinder imbalance that require careful controls design. This paper also introduces a model of the HLE that exhibits similar behavior, making it an indispensible tool for controls design. Further, the model's behavior is evaluated over a range of operating conditions currently unobtainable by the experimental setup.

Climate change due to greenhouse gas emissions has led to new vehicle emissions standards which in turn have led to a call for vehicle technologies to meet these standards. Modeling of vehicle fuel consumption and emissions emerged as an effective tool to help in developing and assessing such technologies, to help in predicting aggregate vehicle fuel consumption and emissions, and to complement traffic simulation models. The paper identifies the current state of the art on vehicle fuel consumption and emissions modeling and its utilization to test the environmental impact of the Intelligent Transportation Systems (ITS)’ measures and to evaluate transportation network improvements. The study presents the relevant models to ITS in the key classifications of models in this research area. It demonstrates that the trends of vehicle fuel consumption and emissions provided by current models generally do satisfactorily replicate field data trends.

A Location-Aware Adaptive Vehicle Dynamics System (LAAVDS) is developed to assist the driver in maintaining vehicle handling capabilities through various driving maneuvers. An integral part of this System is an Intervention Strategy that uses a novel measure of handling capability, the Performance Margin, to assess the need to intervene. Through this strategy, 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. This work develops one means to alter the future vehicle states: modulating the driver's brake commands. This control strategy must be considered in relationship to changes in the throttle commands. Three key elements of this strategy are developed in this work.

Dynamic vehicle loads play critical roles for automotive controls including battery management, transmission shift scheduling, distance-to-empty predictions, and various active safety systems. Accurate real-time estimation of vehicle loads such as those due to vehicle mass and road grade can thus improve safety, efficiency, and performance. While several estimation methods have been proposed in literature, none have seen widespread adoption in current vehicle technologies despite their potential to significantly improve automotive controls. To understand and bridge the gap between research development and wider adoption of real-time load estimation, this paper assesses the accuracy and performance of four estimation methods that predict vehicle mass and/or road grade.

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.

Forward Collision Warning (FCW) and Lane Departure Warning (LDW) systems are two active safety systems that have recently been added to the U.S. New Car Assessment Program (NCAP) evaluation. Vehicles that pass confirmation tests may advertise the presence of FCW and LDW alongside the vehicle's star safety rating derived from crash tests. This paper predicts the number of crashes and injured drivers that could be prevented if all vehicles in the U.S. fleet were equipped with production FCW and/or LDW systems. Models of each system were developed using the test track data collected for 16 FCW and 10 LDW systems by the NCAP confirmation tests. These models were used in existing fleetwide benefits models developed for FCW and LDW. The 16 FCW systems evaluated could have potentially prevented between 9% and 53% of all rear-end collisions and prevented between 19% and 60% of injured (MAIS2+) drivers. Earlier warning times prevented more warnings and injuries.

The purpose of this paper is to demonstrate the impact of low- floor bus seating configuration, passenger load factor (PLF) and passenger characteristics on individual boarding and disembarking (B-D) times -a key component of vehicle dwell time and overall transit system performance. A laboratory study was conducted using a static full-scale mock-up of a low-floor bus. Users of wheeled mobility devices (n=48) and walking aids (n=22), and visually impaired (n=17) and able-bodied (n=17) users evaluated three bus layout configurations at two PLF levels yielding information on B-D performance. Statistical regression models of B-D times helped quantify relative contributions of layout, PLF, and user characteristics viz., impairment type, power grip strength, and speed of ambulation or wheelchair propulsion. Wheeled mobility device users, and individuals with lower grip strength and slower speed were impacted greater by vehicle design resulting in increased dwell time.

This study was designed to investigate how the spectral power distribution (SPD) of LED headlamps (including correlated color temperature, CCT) affects both objective driving performance and subjective responses of drivers. The results of this study are not intended to be the only considerations used in choosing SPD, but rather to be used along with results on how SPD affects other considerations, including visibility and glare. Twenty-five subjects each drove 5 different headlamps on each of 5 experimental vehicles. Subjects included both males and females, in older (64 to 85) and younger (20 to 32) groups. The 5 headlamps included current tungsten-halogen (TH) and high-intensity discharge (HID) lamps, along with three experimental LED lamps, with CCTs of approximately 4500, 5500, and 6500 K. Driving was done at night on public roads, over a 21.5-km route that was selected to include a variety of road types.

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.