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Mechanisms of NH₃ generation using LNT-like catalysts have been studied in a bench reactor over a wide range of temperatures, flow rates, reformer catalyst types and synthetic exhaust-gas compositions. The experiments showed that the on board production of sufficient quantities of ammonia on board for SCR operation appeared feasible, and the results identified the range of conditions for the efficient generation of ammonia. In addition, the effects of reformer catalysts using the water-gas-shift reaction as an in-situ source of the required hydrogen for the reactions are also illustrated. Computations of the NH₃ and NOx kinetics have also been carried out and are presented. Design and impregnation of the SCR catalyst in proximity to the ammonia source is the next logical step. A heated synthetic-exhaust gas flow bench was used for the experiments under carefully controlled simulated exhaust compositions.

Knowledge mapping is a first and mandatory step in creation of system architecture. This paper considers the conceptual modeling of automotive systems, and discusses the creation of a knowledge-based model with respect to the Object Process Methodology an approach used in designing intelligent systems by depicting them using object models and process models. With this knowledge, systems engineer should consider what a product is comprised of (its structure), how it operates (its dynamics), and how it interacts with the environment. As systems have become more complex, a prevalent problem in systems development has been the number of accruing errors. A clearly defined and consistent mapping of knowledge regarding structure, operation and interaction is necessary to construct an effective and useful system. An interactive, iterative and consistent method is needed to cope with this complex and circular problem.

This paper assesses the potential improvement of automotive powertrain technologies 25 years into the future. The powertrain types assessed include naturally-aspirated gasoline engines, turbocharged gasoline engines, diesel engines, gasoline-electric hybrids, and various advanced transmissions. Advancements in aerodynamics, vehicle weight reduction and tire rolling friction are also taken into account. The objective of the comparison is the potential of anticipated improvements in these powertrain technologies for reducing petroleum consumption and greenhouse gas emissions at the same level of performance as current vehicles in the U.S.A. The fuel consumption and performance of future vehicles was estimated using a combination of scaling laws and detailed vehicle simulations. The results indicate that there is significant potential for reduction of fuel consumption for all the powertrains examined.

The existing vehicle designs exhibit a high level of coupling. For instance the coupling in the suspension and steering systems manifests itself through the change in wheel alignment parameters (WAP) due to suspension travel. This change in the WAP causes directional instability and tire-wear. The approach of the industry to solve this problem has been twofold. The first approach has been optimization of suspension link lengths to reduce the change in WAP to zero. Since this is not possible with the existing architecture, the solution used is the optimization of the spring stiffness K to get a compromise solution for comfort (which requires significant suspension travel and hence a soft spring) and directional stability (which demands least possible change in wheel alignment parameters and hence a stiff spring).

This paper presents the results of a study of how people interacted with a production voice-command based interface while driving on public roadways. Tasks included phone contact calling, full address destination entry, and point-of-interest (POI) selection. Baseline driving and driving while engaging in multiple-levels of an auditory-vocal cognitive reference task and manual radio tuning were used as comparison points. Measures included self-reported workload, task performance, physiological arousal, glance behavior, and vehicle control for an analysis sample of 48 participants (gender balanced across ages 21-68). Task analysis and glance measures confirm earlier findings that voice-command interfaces do not always allow the driver to keep their hands on the wheel and eyes on the road, as some assume.

Semi-active suspension systems have traditionally used accelerometers mounted on the wheel and body to sense vehicle motion. However, the cost and weight of these sensors and their associated bracketry and wiring must be considered when deciding to adopt a semi-active suspension system on a particular vehicle. In previous report [1], Authors have described a Bi-Linear Optimal control algorithm [2] by which sprung mass motion is estimated using height sensor signals and a Kalman filter. Such an algorithm would eliminate the need for additional accelerometers and their associated hardware, resulting in a cheaper and lighter system. In this report, the Authors propose a method of improved ride comfort and reducing tuning time of this algorithm by improving the sprung mass motion estimation method.

The quest for higher efficiency and performance of automotive vehicles requires application of materials with high strength, stiffness and lower weight in their construction. Particulate-reinforced aluminum-matrix composites are cost-competitive materials, which can meet these requirements. MMCC, Inc. has been optimizing particulate-reinforced alloy systems and developing the Advanced Pressure Infiltration Casting (APIC™) process for the manufacture of components from these materials. This paper discusses the results of a recent study in which composites reinforced with 55 vol.% alumina were cast using two sizes of alumina particulate and eight different matrix alloys based on Al-4.5 wt.% Cu with varying amounts of silicon and magnesium. Optimum heat treatments for each alloy were determined utilizing microhardness studies. The tensile strength and fracture toughness were evaluated as a function of alloy chemistry, particulate size, and heat treatment.

In this paper we investigate the optimal forming of conical cups of AL 2008-T4 through the use of real-time process control. We consider a flat, frictional binder the force of which can be determined precisely through closed-loop control. Initially the force is held constant throughout the forming of the cup, and various levels of force are tested experimentally and with numerical simulation. Excellent agreement between experiment and simulation is observed. The effects of binder force on cup shape, thickness distribution, failure mode and cup failure height are investigated, and an “optimal” constant binder force is determined. For this optimal case, the corresponding punch force is recorded as a function of punch displacement and is used in subsequent closed-loop control experiments. In addition to the constant force test, a trial variable binder force test was performed to extend the failure height beyond that obtained using the “optimal” constant force level.

This paper presents a numerical model of the rotational and lateral dynamics of the piston (secondary motion) and piston slap in mixed lubrication. Piston dynamic behavior, frictional and impact forces are predicted as functions of crank angle. The model considers piston skirt surface waviness, roughness, skirt profile, thermal and mechanical deformations. The model considers partially-flooded skirt and calculates the pressure distributions and friction in the piston skirt region for both hydrodynamic and boundary lubrication. Model predictions are compared with measurements of piston position using gap sensors in a single-cylinder engine and the comparison between theory and measurement shows remarkable agreement.

Cranking and startup fuel control has become increasingly important due to ever tightening emission requirements. Additionally, engine-off strategies during idle will require substantially more engine startup events with the associated need for very clean starts. Thus, knowledge of an engine's Air-Fuel Ratio (AFR) during its early cycles is necessary in order to optimize cranking and startup fueling. This paper examines and compares two methods of measuring an engine's AFR during engine startup (approximately the first second of operation); an in-cylinder technique using a Fast Flame Ionization Detector (FFID) and the conventional exhaust based Universal Exhaust Gas Oxygen (UEGO) sensor method. Engine starts using a Ford Zetec engine were performed at three different temperatures (0, 20 and 90 C) as well as different initial engine starting positions.

Reliable means for on-board detection of particulate filter failures or malfunctions are needed to meet diagnostics (OBD) requirements. Detecting these failures, which result in tailpipe particulate matter (PM) emissions exceeding the OBD limit, over all operating conditions is challenging. Current approaches employ differential pressure sensors and downstream PM sensors, in combination with particulate filter and engine-out soot models. These conventional monitors typically operate over narrowly-defined time windows and do not provide a direct measure of the filter’s state of health. In contrast, radio frequency (RF) sensors, which transmit a wireless signal through the filter substrate provide a direct means for interrogating the condition of the filter itself.

With the recent advancement in sensing and controller technologies architecture design of an autonomous driving system becomes an important issue. Researchers have been developing different sensors and data processing technologies to solve the issues associated with fast processing, diverse weather, reliability, long distance recognition performance, etc. Necessary considerations of diverse traffic situations and safety factors of autonomous driving have also increased the complexity of embedded software as well as architecture of autonomous driving. In these circumstances, there are almost countless numbers of possible architecture designs. However, these design considerations have significant impacts on cost, controllability, and system reliability. Thus, it is crucial for the designers to make a challenging and critical design decision under several uncertainties during the conceptual design phase.

We report on a feasibility study of an optical micro-electro-mechanical systems (MEMS) flow sensor to measure flow rate using Moiré fringe displacement of a floating element. Due to constraints on weight, power, and size for space environmental systems, the development of sensor components that minimize the equivalent systems mass (ESM) while maintaining or exceeding required specifications is highly desirable. A feature of the optical detection method is a physical separation of electrical components from the flow stream. The geometric Moiré fringe shift optically amplifies small displacements by the ratio of the fringe pitch to the movable grating pitch that is detected using an external CCD imager, providing an electrically isolated, robust, direct scheme for detecting flow from shear stress induced displacement.