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This paper quantifies the potential of electric propulsion systems to reduce petroleum use and greenhouse gas (GHG) emissions in the 2030 U.S. light-duty vehicle fleet. The propulsion systems under consideration include gasoline hybrid-electric vehicles (HEVs), plug-in hybrid vehicles (PHEVs), fuel-cell hybrid vehicles (FCVs), and battery-electric vehicles (BEVs). The performance and cost of key enabling technologies were extrapolated over a 25-30 year time horizon. These results were integrated with software simulations to model vehicle performance and tank-to-wheel energy consumption. Well-to-wheel energy and GHG emissions of future vehicle technologies were estimated by integrating the vehicle technology evaluation with assessments of different fuel pathways. The results show that, if vehicle size and performance remain constant at present-day levels, these electric propulsion systems can reduce or eliminate the transport sector's reliance on petroleum.

Comparisons have been made between dual-fuel (80% port-injection gasoline and 20% direct-injection diesel by mass) Highly Premixed Charge Combustion (HPCC) and blended-fuel (80% gasoline and 20% diesel) Low Temperature Combustion (LTC) modes on a 1-L single-cylinder test engine. In the HPCC mode, both early-injection (E-HPCC) and late-injection (L-HPCC) of diesel have been used. The comparisons have been conducted with a fixed fuel injection rate of 50 mg/cycle at 1500 rpm, and with the combustion phasing fixed (by adjusting the injection timing) so that the 50% heat release point (CA50) is at 8° ATDC. The rapid heat release process of LTC leads to the highest maximum pressure rise rate (MPRR). A two-peak heat release process is observed in L-HPCC, resulting in a lower MPRR. The heat release rate and MPRR values for the E-HPCC are comparable to the L-HPCC values. The EHPCC mode provides the lowest NOX emission. The soot emissions for all three modes are low.

A method for detecting drivers' intentions is essential to facilitate operating mode transitions between driver and driver assistance systems. We propose a driver behavior recognition method using Hidden Markov Models (HMMs) to characterize and detect driving maneuvers and place it in the framework of a cognitive model of human behavior. HMM-based steering behavior models for emergency and normal lane changes as well as for lane keeping were developed using a moving base driving simulator. Analysis of these models after training and recognition tests showed that driver behavior modeling and recognition of different types of lane changes is possible using HMMs.

The challenge of developing a robust, real-time driver gaze classification system is that it has to handle difficult edge cases that arise in real-world driving conditions: extreme lighting variations, eyeglass reflections, sunglasses and other occlusions. We propose a single-camera end-toend framework for classifying driver gaze into a discrete set of regions. This framework includes data collection, semi-automated annotation, offline classifier training, and an online real-time image processing pipeline that classifies the gaze region of the driver. We evaluate an implementation of each component on various subsets of a large onroad dataset. The key insight of our work is that robust driver gaze classification in real-world conditions is best approached by leveraging the power of supervised learning to generalize over the edge cases present in large annotated on-road datasets.

An aerodynamic model of the entrainment of the head wall quench layer during blowdown and exhaust of an internal combustion engine has been developed. The model may be used to calculate the time resolved concentration and mass flowrate of hydrocarbons (HC) in the exhaust, from a knowledge of engine geometry and operating conditions. It predicts that the area As from which HC are swept will be proportional to the cube root of the ratio of the quench layer thickness δq to the thickness of the viscous boundary layer δv. Since the mass of HC emitted is proportional to the product of the HC density ρHC, the area As and the thickness δq, the HC emissions will be proportional to the product ρHC δq4/3 and this is the most important factor determining the emissions.

The use of hydrogen as a fuel supplement for lean-burn engines at higher compression ratios has been studied extensively in recent years, with good promise of performance and efficiency gains. With the advances in reformer technology, the use of a gaseous fuel stock, comprising of substantially higher fractions of hydrogen and other flammable reformate species, could provide additional improvements. This paper presents the performance and emission characteristics of a gas mixture of equal volumes of hydrogen, CO, and methane. It has recently been reported that this gas mixture can be produced by reforming of ethanol at comparatively low temperature, around 300C. Experiments were performed on a 1.8-liter passenger-car Nissan engine modified for single-cylinder operation. Special pistons were made so that compression ratios ranging from CR= 9.5 to 17 could be used. The lean limit was extended beyond twice stoichiometric (up to lambda=2.2).

A novel engine management strategy for achieving fast catalyst light-off without the use of an exhaust air pump in a port-fuel-injected, spark ignition engine was developed. A conventional 4-cylinder engine was operated with three cylinders running rich and the fourth one as an air pump to supply air to the exhaust manifold. Under steady-state cold coolant conditions, this strategy achieved near total oxidation of CO and HC with sufficiently retarded spark timing, resulting in a 400% increase in feedgas enthalpy flow and a 90% reduction in feedgas HC emissions compared to conventional operation. The strategy was also evaluated for crank starts. Using the existing engine hardware, implementing the strategy resulted in a reduction in catalyst light-off time from 28.0 seconds under conventional operation to 9.1 seconds.

A fuel volatility model based on the major species present in the fuel has been formulated. The model accurately predicts the ASTM distillation curves and Reid Vapor Pressure for hydrocarbon fuels. The model may be used to assess the fuel effects on the extent of evaporation and the vapor composition in the mixture preparation process.

Accurately predicting real-world vehicle energy consumption is essential for optimizing vehicle designs, enhancing energy efficiency, and developing effective energy management strategies. This paper presents a data-driven approach that utilizes machine learning techniques and a comprehensive dataset of vehicle parameters and environmental factors to create precise energy consumption prediction models. The methodology involves recording real-world vehicle data using data loggers to extract information from the CAN bus systems for ICE and hybrid electric, as well as hydrogen and battery fuel cell vehicles. Data cleaning and cycle-based analysis are employed to process the dataset for accurate energy consumption prediction. This includes cycle detection and analysis using methods from statistics and signal processing, and then pattern recognition based on these metrics.

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.

Currently, states that are out of compliance with the National Ambient Air Quality Standards must, according to the Clean Air Act Amendments of 1990 (CAAA), develop and implement control strategies that demonstrate specific degrees of reduction in emissions-with the degree of reduction depending upon the severity of the problem. One tool that has been developed to aid regulators in both deciding an appropriate course of action and to demonstrate the desired reductions in mobile emissions is EPA's Mobile 5a emission estimation model. In our study, Mobile 5a has been used to examine the effects of regulatory strategies, as applied to the Northeast United States, on vehicle emissions under worst-case ozone-forming conditions.

Non-petroleum based liquid fuels are essential for reducing oil dependence and greenhouse gas generation. Increased substitution of alcohol fuel for petroleum based fuels could be achieved by 1) use in high efficiency spark ignition engines that are employed for heavy duty as well as light duty operation and 2) use of methanol as well as ethanol. Methanol is the liquid fuel that is most efficiently produced from thermo-chemical gasification of coal, natural gas, waste or biomass. Ethanol can also be produced by this process but at lower efficiency and higher cost. Coal derived methanol is in limited initial use as a transportation fuel in China. Methanol could potentially be produced from natural gas at an economically competitive fuel costs, and with essentially the same greenhouse gas impact as gasoline. Waste derived methanol could also be an affordable low carbon fuel.

This paper provides an overview of spark-ignition engine unburned hydrocarbon emissions mechanisms, and then uses this framework to relate measured engine-out hydrocarbon emission levels to the processes within the engine from which they result. Typically, spark-ignition engine-out HC levels are 1.5 to 2 percent of the gasoline fuel flow into the engine; about half this amount is unburned fuel and half is partially reacted fuel components. The different mechanisms by which hydrocarbons in the gasoline escape burning during the normal engine combustion process are described and approximately quantified. The in-cylinder oxidation of these HC during the expansion and exhaust processes, the fraction which exit the cylinder, and the fraction oxidized in the exhaust port and manifold are also estimated.

To meet future particle mass and particle number standards, gasoline vehicles may require particle control, either by way of an exhaust gas filter and/or engine modifications. Soot levels for gasoline engines are much lower than diesel engines; however, non-combustible material (ash) will be collected that can potentially cause increased backpressure, reduced power, and lower fuel economy. The purpose of this work was to examine the ash loading of gasoline particle filters (GPFs) during rapid aging cycles and at real time low mileages, and compare the filter performances to both fresh and very high mileage filters. Current rapid aging cycles for gasoline exhaust systems are designed to degrade the three-way catalyst washcoat both hydrothermally and chemically to represent full useful life catalysts. The ash generated during rapid aging was low in quantity although similar in quality to real time ash. Filters were also examined after a low mileage break-in of approximately 3000 km.

An analysis method for characterizing fuel behavior during spark-ignition engine starting has been developed and applied to several sets of start-up data. The data sets were acquired from modern production vehicles during room temperature engine start-up. Two different engines, two control schemes, and two engine temperatures (cold and hot) were investigated. A cycle-by-cycle mass balance for the fuel was used to compare the amount of fuel injected with the amount burned or exhausted as unburned hydrocarbons. The difference was measured as “fuel unaccounted for”. The calculation for the amount of fuel burned used an energy release analysis of the cylinder pressure data. The results include an overview of starting behavior and a fuel accounting for each data set Overall, starting occurred quickly with combustion quality, manifold pressure, and engine speed beginning to stabilize by the seventh cycle, on average.

The direct injection spark-ignition engine is the only internal combustion engine with the potential to equal the efficiency of the diesel and to tolerate a wide range of fuel types and fuel qualities without deterioration of performance. However, this engine has low combustion efficiency and excessive hydrocarbon emissions when operating at light load. In this paper, potential sources of hydrocarbon emissions during light load operation are postulated and analyzed. The placement of fuel away from the primary combustion process in conjunction with a lack of secondary burnup are isolated as important hydrocarbon emissions mechanisms. Analyses show that increasing cylinder gas temperatures can improve secondary burnup of fuel which would reduce hydrocarbon emissions. Practical means to achieve this include higher compression ratio and use of ceramic parts in the combustion chamber.

The NOx emissions during the crank-start and cold fast-idle phases of a GDI engine are analyzed in detail. The NOx emissions of the first 3 firing cycles are studied under a wide set of parameters including the mass of fuel injected, start of injection, and ignition timing. The results show a strong dependence of the NOx emissions with injection timing; they are significantly reduced as the mixture is stratified. The impact of different valve timings on crank-start NOx emissions was analyzed. Late intake and early exhaust timings show similar potential for NOx reduction; 26-30% lower than the baseline. The combined strategy, resulting in a large symmetric negative valve overlap, shows the greatest reduction; 59% lower than the baseline. The cold fast-idle NOx emissions were studied under different equivalence ratios, injection strategies, combustion phasing, and valve timings. Slightly lean air-fuel mixtures result in a significant reduction of NOx.

While metal fiber filters have successfully shown a high degree of particle retention functionality for various sizes of diesel engines with a low pressure drop and a relatively high filtration efficiency, little is known about the effects of lubricant-derived ash on the fiber filter systems. Sintered metal fiber filters (SMF-DPF), when used downstream from a diesel engine, effectively trap and oxidize diesel particulate matter via an electrically heated regeneration process where a specific voltage and current are applied to the sintered alloy fibers. In this manner the filter media essentially acts as a resistive heater to generate temperatures high enough to oxidize the carbonaceous particulate matter, which is typically in excess of 600°C.

Ash, primarily derived from diesel engine lubricants, accumulates in diesel particulate filters directly affecting the filter's pressure drop sensitivity to soot accumulation, thus impacting regeneration frequency and fuel economy. After approximately 33,000 miles of equivalent on-road aging, ash comprises more than half of the material accumulated in a typical cordierite filter. Ash accumulation reduces the effective filtration area, resulting in higher local soot loads toward the front of the filter. At a typical ash cleaning interval of 150,000 miles, ash more than doubles the filter's pressure drop sensitivity to soot, in addition to raising the pressure drop level itself. In order to evaluate the effects of lubricant-derived ash on DPF pressure drop performance, a novel accelerated ash loading system was employed to generate the ash and load the DPFs under carefully-controlled exhaust conditions.

The gasoline direct injection (GDI) engine particulate emission sources are assessed under cold start conditions: the fast idle and speed/load combinations representative of the 1st acceleration in the US FTP. The focus is on the accumulation mode particle number (PN) emission. The sources are non-fuel, combustion of the premixed charge, and liquid fuel film. The non-fuel emissions are measured by operating the engine with premixed methane/air or hydrogen/air. Then the PN level is substantially lower than what is obtained with normal GDI operation; thus non-fuel contribution to PN is small. When operating with stoichiometric premixed gasoline/air, the PN level is comparable to the non-fuel level; thus premixed-stoichiometric mixture combustion does not significantly generate particulates. For fuel rich premixed gasoline/air, PN increases dramatically when lambda is less than 0.7 to 0.8.