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While gasoline surrogate development has progressed in the areas of more complex surrogate mixtures and in kinetic modeling tools and mechanism development, it is generally recognized that further development is still needed. This paper represents a small step in supporting this development by providing comparisons between experimental engine data and surrogate-based kinetic models. In our case, the HCCI engine data comes from a port-injected, single-cylinder research engine with intake-air heating for combustion phasing control. Timing sweeps were run at constant fuel rate for three market gasolines and five surrogate mixtures. Modeling was done using the CHEMKIN software with a gasoline mechanism set containing 1440 species and 6572 reactions. Five pure compounds were selected for the surrogate blends and include iso-octane, n-heptane, toluene, methylcyclohexane, and 1-hexene.

This project team conducted a life-cycle-based environmental evaluation of new, lightweight materials (e.g., titanium, magnesium) used in two concept 3XVs -- i.e., automobiles that are three times more fuel efficient than today's automobiles -- that are being designed and developed in support of the Partnership for a New Generation of Vehicles (PNGV) program. The two concept vehicles studied were the DaimlerChrysler ESX2 and the Ford P2000. Data for this research were drawn from a wide range of sources, including: the two automobile manufacturers; automobile industry reports; government and proprietary databases; past life-cycle assessments; interviews with industry experts; and models.

The crush performance of lightweight composite automotive structures varies significantly between static and dynamic test conditions. This paper discusses the development of a new dynamic testing facility that can be used to characterize crash performance at high loads and constant speed. Previous research results from the Energy Management Working Group (EMWG) of the Automotive Composites Consortium (ACC) showed that the static crush resistance of composite tubes can be significantly greater than dynamic crush results at speeds greater than 2 m/s. The new testing facility will provide the unique capability to crush structures at high loads in the intermediate velocity range. A novel machine control system was designed and projections of the machine performance indicate its compliance with the desired test tolerances. The test machine will be part of a national user facility at the Oak Ridge National Laboratory (ORNL) and will be available for use in the summer of 2002.

Plug-in hybrid electric vehicle (PHEV) technologies have the potential for considerable petroleum consumption reductions, possibly at the expense of increased tailpipe emissions due to multiple “cold” start events and improper use of the engine for PHEV specific operation. PHEVs operate predominantly as electric vehicles (EVs) with intermittent assist from the engine during high power demands. As a consequence, the engine can be subjected to multiple cold start events. These cold start events may have a significant impact on the tailpipe emissions due to degraded catalyst performance and starting the engine under less than ideal conditions. On current hybrid electric vehicles (HEVs), the first cold start of the engine dictates whether or not the vehicle will pass federal emissions tests. PHEV operation compounds this problem due to infrequent, multiple engine cold starts.

A systems-level modeling framework developed to estimate the life cycle cost of medium- and heavy-duty trucks is discussed in this paper. Costs are estimated at a resolution of five major subsystems and 30+ subsystems, each representing a specific manufacturing technology. Interrelationships among various subsystems affecting cost are accounted for. Results of a specific Class 8 truck are finally discussed to demonstrate the modeling framework's capability, including the analysis of cost-effectiveness of some of the competing alternative system design options being considered by the industry today.

Thermal conductivity detection has long been used in gas chromatography to detect hydrogen and other diatomic gases in a gas sample. Thermal conductivity instruments that are not coupled to gas chromatographs are useful for detecting hydrogen in binary gas mixtures, but suffer from significant cross-interference from other gas species that are separated when the detector is used with a gas chromatograph. This study reports a method for using a commercially-available thermal conductivity instrument to detect and quantify hydrogen in a diesel exhaust stream. The instrument time response of approximately 40 seconds is sufficient for steady-state applications. Cross-interference from relevant gas species are quantified and discussed. Measurement uncertainty associated with the corrections for the various species is estimated and practical implications for use of the instrument and method are discussed.

Battery electric vehicles (BEV) in heavy duty (HD) commercial freight transport face challenging technoeconomic barriers to adoption. Specifically, beyond safety and compliance, fleet and operational logistics require both high up-time and parity with diesel system productivity/Total Cost of Ownership (TCO) to enable strong adoption of electrified powertrains. At present, relatively high energy storage prices coupled with the increased weight of BEV systems limit the practicality of HD commercial freight transport to shorter range applications, where smaller batteries will suffice for the mission energy requirements (single operational shift). This paper presents an approach to extend the feasibility of BEV HD trucking for a broad range of applications.

The widespread adoption of boosted, downsized SI engines has brought pre-ignition phenomena into greater focus, as the knock events resulting from pre-ignitions can cause significant hardware damage. Much attention has been given to understanding the causes of pre-ignition and identify lubricant or fuel properties and engine design and calibration considerations that impact its frequency. This helps to shift the pre-ignition limit to higher specific loads and allow further downsizing but does not fundamentally eliminate the problem. Real-time detection and mitigation of pre-ignition would thus be desirable to allow safe engine operation in pre-ignition-prone conditions. This study focuses on advancing the time of detection of pre-ignition in an engine cycle where it occurs.

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.

A hybrid LNT+SCR system is used to control NOx from a light-duty diesel engine with in-cylinder regeneration controls. A diesel oxidation catalyst and diesel particulate filter are upstream of the LNT and SCR catalysts. Ultraviolet (UV) adsorption spectroscopy performed directly in the exhaust path downstream of the LNT and SCR catalysts is used to characterize NH3 production and utilization in the system. Extractive exhaust samples are analyzed with FTIR and magnetic sector mass spectrometry (H2) as well. Furthermore, standard gas analyzers are used to complete the characterization of exhaust chemistry. NH3 formation increases strongly with extended regeneration (or “over regeneration”) of the LNT, but the portion of NOx reduction occurring over the SCR catalyst is limited by the amount of NH3 produced as well as the amount of NOx available downstream of the LNT. Control of lean-rich cycling parameters enables control of the ratio of NOx reduction between the LNT and SCR catalysts.

A modified Mercedes 1.7-liter, direct-injection diesel engine was operated in both normal and high-efficiency clean combustion (HECC) combustion modes. Four steady-state engine operating points that were previously identified by the Ad-hoc fuels working group were used as test points to allow estimation of the hot-start FTP-75 emissions levels in both normal and HECC combustion modes. The results indicate that operation in HECC modes generally produce reductions in NOX and PM emissions at the expense of CO, NMHC, and H2CO emissions. The FTP emissions estimates indicate that aftertreatment requirements for NOX are reduced, while those for PM may not be impacted. Cycle-average aftertreatment requirements for CO, NMHC, and H2CO may be challenging, especially at the lowest temperature conditions.

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.

Continuous efforts to develop a lightweight alloy suitable for the most demanding applications in automotive industry resulted in a number of advanced aluminum (Al) and magnesium alloys and manufacturing routes. One example of this is the application of 319 Al alloy for production of 3.6L V6 gasoline engine blocks. Aluminum is sand cast around Fe-liner cylinder inserts, prior to undergoing the T7 heat treatment process. One of the critical factors determining the quality of the final product is the type, level, and profile of residual stresses along the Fe liners (or extent of liner distortion) that are always present in a cast component. In this study, neutron diffraction was used to characterize residual stresses along the Al and the Fe liners in the web region of the cast engine block. The strains were measured both in Al and Fe in hoop, radial, and axial orientations. The stresses were subsequently determined using generalized Hooke's law.

As interest has grown in diesel emissions and diesel engine aftertreatment, so has the importance of analyzing all components of the exhaust. One of the more costly and difficult measurements to make is the collection and analysis of semivolatile organic compounds (SOCs) in the exhaust. These compounds include alkane and alkenes from C12-C24, and the 2-5 ring polycyclic aromatic hydrocarbons (PAH). These compounds can be present in both the particulate (i.e. on the filter) and gaseous phase, and cannot be collected with bag samples. Typically, a sorbent is used downstream of the particulate collection filters to collect these compounds. Sorbent phases include polyurethane foam (PUF), Tenax™, XAD-type resins, and activated carbon. The SOCs are removed from the sorbent either by solvent extraction (PUF and XAD) or thermal desorption (Tenax™ and activated carbon). Each of these methods have advantages and disadvantages.

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.

Accurately predicting the fuel savings that can be achieved with the implementation of various technologies developed for fuel efficiency can be very challenging, particularly when considering combinations of technologies. Differences in the usage of highway vehicles can strongly influence the benefits realized with any given technology, which makes generalizations about fuel savings inappropriate for different vehicle applications. A model has been developed to estimate the potential for reducing fuel consumption when advanced efficiency technologies, or combinations of these technologies, are employed on highway vehicles, particularly medium- and heavy-duty trucks. The approach is based on a tractive energy analysis applied to drive cycles representative of the vehicle usage, and the analysis specifically accounts for individual energy loss factors that characterize the technologies of interest.

Downsized turbocharged engines have been increasingly popular in modern light-duty vehicles due to their fuel efficiency benefits. However, high power density in such engines is achieved thanks to high in-cylinder pressure and temperature conditions that increase knock propensity. Next-cycle control has been studied as a method to reduce the damaging effects of knock by operating the engine in a low knock probability condition. This exploratory study looks at the feasibility of in-cycle knock prediction as a tool for advanced knock control algorithms. A methodology is proposed to 1) choose in-cycle features of the pressure trace that highly correlate with knock events and 2) train artificial neural networks to predict in-cycle knock events before knock onset. The methodology was validated at different operating conditions and different levels of generalization. Precision and recall were used as metrics to evaluate the binary classifier.