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The demand for improved fuel economy in both cars and trucks has emphasized the need for lighter weight components. The application of high strength steel to wheels, both rim and disc, represents a significant opportunity for the automotive industry. This paper discusses the Ranger HSLA wheel program that achieved a 9.7 lbs. per vehicle weight savings relative to a plain carbon steel wheel of the same design. It describes the Ranger wheel specifications, the material selection, the metallurgical considerations of applying HSLA to wheels, and HSLA arc and flash butt welding. The Ranger wheel design and the development of the manufacturing process is discussed, including design modifications to accommodate the lighter gage. The results demonstrate that wheels can be successfully manufactured from low sulfur 60XK HSLA steel in a conventional high volume process (stamped disc and rolled rim) to meet all wheel performance requirements and achieve a significant weight reduction.

The affordability of today's and future advanced technology vehicles (i.e., diesel, hybrid, and fuel cell) developed for improved fuel economy remains a concern with respect to final consumer acceptance. The automotive system cost model (ASCM) developed for the production cost estimates at a level of five major subsystems and 35+ components, has been used here to address the affordability issue of advanced technology vehicles. Scenarios encompassing five alternative powertrain and three body options for a mid-size vehicle under two different timeframes (i.e., 2002 and 2010) were considered to determine the cost-effectiveness of among the competing technology options within the same timeframe and between the two timeframes.

Four vehicle fleets, consisting of 3 to 4 vehicles each, were emission tested on a 48″ roll chassis dynamometer using both the FTP urban dynamometer driving cycle and the REP05 driving cycle. The REP05 cycle was developed to test vehicles under high speed and high load conditions not included in the FTP. The vehicle fleets consisted of 1989 light-duty gasoline vehicles, 1992-93 limited production FFV/VFV methanol vehicles, 1992-93 compressed natural gas (CNG) vehicles and their gasoline counterparts, and a 1992 production and two prototype ethanol FFV/VFV vehicles. All vehicles (except the dedicated CNG vehicles) were tested using Auto/Oil AQIRP fuels A and C2. Other fuels used were M85 blended from A and C2, E85 blended from C1, which is similar to C2 but without MTBE, and four CNG fuels representing the range of in-use CNG fuels. In addition to bag measurements, tailpipe exhaust concentration and A/F data were collected once per second throughout every test.

A model is presented which incorporates the key mechanisms in the formation and reduction of unburned HC emissions from spark ignited engines. The model includes the effects of piston crevice volume, oil layer absorption / desorption, partial burns, and in-cylinder and exhaust port oxidation. The mechanism for the filling and emptying of the piston crevice takes into account the location of the flame front so that the flow of both burned gas and unburned gas is recognized. Oxidation of unburned fuel is calculated with a global, Arrhenius-type equation. A newly developed submodel is included which calculates the amount of unburned fuel to be added to the cylinder as a result of partial burns. At each crankangle, the submodel compares the rate of change of the burned gas volume to the rate of change of the cylinder volume.

Although there was a safety awareness from the earliest days of the automobile, systematic approaches to designing for safety became more widespread after 1950 when large numbers of vehicles came into use in both the United States and Europe, and governments in both continents undertook a widespread highway development. Industry response to safety objectives and also to government regulation has produced a large number of safety enhancing engineering developments, including radial tires, disc brakes, anti-lock brakes, improved vehicle lighting systems, better highway sign support poles, padded instrument panels, better windshield retention systems, collapsible hood structures, accident sensitive fuel pump shut-off valves, and other items. A significant development was the design of the energy absorbing front structures.

Combustion flame geometry calculation is a critical task in the design and analysis of combustion engine chamber. Combustion flame directly influences the fuel economy, engine performance and efficiency. Currently, many of the flame geometry calculation methods assume certain specific chamber and piston top shapes and make some approximations to them. Even further, most methods can not handle multiple spark plug set-ups. Consequently, most of the current flame geometry calculation methods do not give accurate results and have some built-in limitations. They are particularly poor for adapting to any kind of new chamber geometry and spark plug set-up design. This report presents a novel methodology which allows the accurate calculation of flame geometry regardless of the chamber geometry and the number of spark plugs. In this methodology, solid models are used to represent the components within the chamber and unique attributes (colors) are attached respectively to these components.

Internal combustion engines are operated under conditions of high exhaust gas recirculation (EGR) to reduce NOx emissions and promote enhanced combustion modes such as HCCI. However, high EGR under certain conditions also promotes nonlinear feedback between cycles, leading to the development of combustion instabilities and cyclic variability. We employ a two-zone phenomenological combustion model to simulate the onset of combustion instabilities under highly dilute conditions and to illustrate the impact of these instabilities on emissions and fuel efficiency. The two-zone in-cylinder combustion model is coupled to a WAVE engine-simulation code through a Simulink interface, allowing rapid simulation of several hundred successive engine cycles with many external engine parametric effects included.

New vehicle control algorithms are needed to meet future emissions and fuel economy mandates that are quite likely to require a measurement of ambient specific humidity (SH). Current practice is to obtain the SH by measurement of relative humidity (RH), temperature and barometric pressure with physical sensors, and then to estimate the SH using a fit equation. In this paper a novel approach is described: a system of neural networks trained to estimate the SH using data that already exists on the vehicle bus. The neural network system, which is referred to as a virtual SH sensor, incorporates information from the global navigation satellite system such as longitude, latitude, time and date, and from the vehicle climate control system such as temperature and barometric pressure, and outputs an estimate of SH. The conclusion of this preliminary study is that neural networks have the potential of being used as a virtual sensor for estimating ambient and intake manifold's SH.

The effects of engine operating conditions on the octane requirement and the resulting knock-limited output were studied on a single cylinder engine using production cylinder heads. A 4-valve cylinder head with port deactivation was used to study the effect of fuel octane, inlet air temperature, coolant temperature, air/fuel ratio, compression ratio and exhaust back pressure. The effect of the thermal environment was studied in more detail using separate cooling systems for the cylinder head and engine block on a 2-valve cylinder head. The results of this study compared closely with results found in the literature even though the engine and/or operating conditions were quite different in many cases.

The small-displacement direct-injection (DI) diesel engine is a prime candidate for future transportation needs because of its high thermal efficiency combined with near term production feasibility. Ford Motor Company and FEV Engine Technology, Inc. are working together with the US Department of Energy to develop a small displacement DI diesel engine that meets the key challenges of emissions, NVH, and power density. The targets for the engine are to meet ULEV emission standards while maintaining a best fuel consumption of 200g/kW-hr. The NVH performance goal is transparency with state-of-the-art, four-cylinder gasoline vehicles. Advanced features are required to meet the ambitious targets for this engine. Small-bore combustion systems enable the downsizing of the engine required for high fuel economy with the NVH advantages a four- cylinder has over a three-cylinder engine.

A structural ceramic diesel engine has the potential to provide low heat rejection and significant improvements in fuel economy. Analytical and experimental evaluations were conducted on the critical elements of this engine. The structural ceramic components, which included the cylinder, piston and pin, operated successfully in a single cylinder engine for over 100 hours. The potential for up to 8-11% improvement in indicated specific fuel consumption was projected when corrections for blow-by were applied. The ringless piston with gas squeeze film lubrication avoided the difficulty with liquid lubricants in the high temperature piston/cylinder area. The resulting reduction in friction was projected to provide an additional 15% improvement in brake specific fuel consumption for a multi-cylinder engine at light loads.

In order to achieve proposed fuel economy requirements, engines must make better use of the available fuel energy. Regardless of how efficient the engine is, there will still be a significant fraction of the fuel energy that is rejected in the exhaust and coolant streams. One viable technology for recovering this waste heat is an Organic Rankine Cycle. This cycle heats a working fluid using these heat streams and expands the fluid through a turbine to produce shaft power. The present work was the development of such a system applied to a light duty diesel engine. This lab demonstration was designed to maximize the peak brake thermal efficiency of the engine, and the combined system achieved an efficiency of 45%. The design of the system is discussed, as are the experimental performance results. The system potential at typical operating conditions was evaluated to determine the practicality of installing such a system in a vehicle.

G-Equation models represent propagating flame fronts with an implicit two-dimensional surface representation (level-set). Level-set methods are fast, as transport source terms for the implicit surface can be solved with finite-volume operators on the finite-volume domain, without having to build the actual surface. However, they include approximations whose practical effects are not properly understood. In this study, we improved the numerics of the FRESCO CFD code’s G-Equation solver and developed a new method to simulate kernel growth using signed distance functions and the analytical sphere-mesh overlap. We analyzed their role for simulating propane/air flames, using three well-established constant-volume configurations: a one-dimensional, freely propagating laminar flame; a disc-shaped, constant-volume swirl combustor; and torch-jet flame development through an orifice from a two-chamber device.

Lean gasoline engines offer greater fuel economy than the common stoichiometric gasoline engine, but the current three way catalyst (TWC) on stoichiometric engines is unable to control nitrogen oxide (NOX) emissions in oxidizing exhaust. For these lean gasoline engines, lean NOX emission control is required to meet existing Tier 2 and upcoming Tier 3 emission regulations set by the U.S. Environmental Protection Agency (EPA). While urea-based selective catalytic reduction (SCR) has proven effective in controlling NOX from diesel engines, the urea storage and delivery components can add significant size and cost. As such, onboard NH3 production via a passive SCR approach is of interest. In a passive SCR system, NH3 is generated over a close-coupled TWC during periodic slightly rich engine operation and subsequently stored on an underfloor SCR catalyst. Upon switching to lean operation, NOX passes through the TWC and is reduced by the stored NH3 on the SCR catalyst.

A commercial three-way catalyst (TWC) was evaluated for ammonia (NH3) generation on a 2.0-liter BMW lean burn gasoline direct injection engine as a component in a passive ammonia selective catalytic reduction (SCR) system. The passive NH3 SCR system is a potential low cost approach for controlling nitrogen oxides (NOX) emissions from lean burn gasoline engines. In this system, NH3 is generated over a close-coupled TWC during periodic slightly rich engine operation and subsequently stored on an underfloor SCR catalyst. Upon switching to lean, NOX passes through the TWC and is reduced by the stored NH3 on the SCR catalyst. NH3 generation was evaluated at different air-fuel equivalence ratios at multiple engine speed and load conditions. Near complete conversion of NOX to NH3 was achieved at λ=0.96 for nearly all conditions studied. At the λ=0.96 condition, HC emissions were relatively minimal, but CO emissions were significant.

An optical-based sensor for detecting particulate matter (PM) in diesel engine exhaust has been demonstrated. The position of the sensor during the experiments was the exhaust manifold prior to the turbocharger. The sensor is constructed of fiber optics which transmit 532-nm laser light into the exhaust pipe and collect backscattered light in a 180° geometry. Due to the optical nature of the probe, PM sensing can occur at high temporal rates. Experiments conducted by changing the fuel injection properties of one cylinder of a four cylinder engine demonstrated that the sensor can resolve cycle dependent events. The feasibility of the probe for examining PM emissions in the exhaust manifold will be discussed.

1Increasing adoption of downsized, boosted, spark-ignition engines has improved vehicle fuel economy, and continued improvement is desirable to reduce carbon emissions in the near-term. However, this strategy is limited by damaging preignition events which can cause hardware failure. Research to date has shed light on various contributing factors related to fuel and lubricant properties as well as calibration strategies, but the causal factors behind an individual preignition cycle remain elusive. If actionable precursors could be identified, mitigation through active control strategies would be possible. This paper uses artificial neural networks to search for identifiable precursors in the cylinder pressure data from a large real-world data set containing many preignition cycles. It is found that while follow-up preignition cycles in clusters can be readily predicted, the initial preignition cycle is not predictable based on features of the cylinder pressure.

A central challenge for efficient auto-ignition controlled low-temperature gasoline combustion (LTGC) engines has been achieving the combustion phasing needed to reach stable performance over a wide operating regime. The negative valve overlap (NVO) strategy has been explored as a way to improve combustion stability through a combination of charge heating and altered reactivity via a recompression stroke with a pilot fuel injection. The study objective was to analyze the thermal and chemical effects on NVO-period energy recovery. The analysis leveraged experimental gas sampling results obtained from a single-cylinder LTGC engine along with cylinder pressure measurements and custom data reduction methods used to estimate period thermodynamic properties. The engine was fueled by either iso-octane or ethanol, and operated under sweeps of NVO-period oxygen concentration, injection timing, and fueling rate.

The variability in gasoline energy content, though most frequently not a consumer concern, is an issue of concern for vehicle manufacturers in demonstrating compliance with regulatory requirements. Advancements in both vehicle technology, test methodology, and fuel formulations have increased the level of visibility and concern with regard to the energy content of fuels used for regulatory testing. The R factor was introduced into fuel economy calculations for vehicle certification in the late 1980s as a means of addressing batch-to-batch variations in the heating value of certification fuels and the resulting variations in fuel economy results. Although previous studies have investigated values of the R factor for modern vehicles through experimentation, subsequent engine studies have made clear that it is difficult to distinguish between the confounding factors that influence engine efficiency when R is being studied experimentally.

As the world's largest auto producer and consumer, China is both the most promising and complex market given the country's rapid economic growth, huge population, and many regional and segment preference differences. This research is aimed at developing data-driven demand models for customer preference analysis and prediction under a competitive market environment. Regional analysis is first used to understand the impact of geographical factors on customer preference. After a comprehensive data exploration, a customer-level mixed logit model is built to shed light on fast-growing vehicle segments in the Chinese auto market. By combining the data of vehicle purchase, consideration, and past choice, cross-shopping behaviors and brand influence are explicitly modeled in addition to the impact of customer demographics, usage behaviors, and attributes of vehicles.