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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.

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.

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.

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.

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.

In this study the authority of the available engine controls are characterized as the high load limit of homogeneous charge compression ignition (HCCI) combustion is approached. A boosted single-cylinder research engine is used and is equipped with direct injection (DI) fueling, a laboratory air handling system, and a hydraulic valve actuation (HVA) valve train to enable negative valve overlap (NVO) breathing. Results presented include engine loads from 350 to 650 kPa IMEPnet and manifold pressure from 98 to 190 kPaa. It is found that in order to increase engine load to 650 kPa IMEPnet, it is necessary to increase manifold pressure and external EGR while reducing the NVO duration. While both are effective at controlling combustion phasing, NVO duration is found to be a "coarse" control while fuel injection timing is a "fine" control.

Low temperature combustion engine technologies are being investigated for high efficiency and low emissions. However, such engine technologies often produce higher engine-out hydrocarbon (HC) and carbon monoxide (CO) emissions, and their operating range is limited by the fuel properties. In this study, two different fuels, a US market gasoline containing 10% ethanol (RON 92 E10) and a higher reactivity gasoline (RON 80 E0), were compared on Delphi’s second generation Gasoline Direct-Injection Compression Ignition (Gen 2.0 GDCI) multi-cylinder engine. The engine was evaluated at three operating points ranging from a light load condition (800 rpm/2 bar IMEPg) to medium load conditions (1500 rpm/6 bar and 2000 rpm/10 bar IMEPg). The engine was equipped with two oxidation catalysts, between which was located the exhaust gas recirculation (EGR) inlet. Samples were taken at engine-out, between the catalysts, and at tailpipe locations.

One challenge in meeting emission regulations with catalytic aftertreatment systems is maintaining the proper catalyst temperatures that enable the catalytic devices to perform the emissions reduction. In this study, in-cylinder techniques are used to actively control the temperature of a catalyzed diesel particulate filter (DPF) in order to raise the DPF temperature to induce particulate oxidation. The performance of four strategies is compared for two different starting DPF temperatures (150°C and 300°C) on a 4-cylinder 1.7-liter diesel engine. The four strategies include: (1) addition of extra fuel injection early in the combustion cycle for all four cylinders, (2) addition of extra fuel injection late in the combustion cycle for all four cylinders, (3) operating one-cylinder with extra fuel injection early in the combustion cycle, and (4) operating one-cylinder with extra fuel injection late in the combustion cycle.

The focus of the present study was to characterize Reactivity Controlled Compression Ignition (RCCI) using a single-fuel approach of gasoline and gasoline mixed with a commercially available cetane improver on a multi-cylinder engine. RCCI was achieved by port-injecting a certification grade 96 research octane gasoline and direct-injecting the same gasoline mixed with various levels of a cetane improver, 2-ethylhexyl nitrate (EHN). The EHN volume percentages investigated in the direct-injected fuel were 10, 5, and 2.5%. The combustion phasing controllability and emissions of the different fueling combinations were characterized at 2300 rpm and 4.2 bar brake mean effective pressure over a variety of parametric investigations including direct injection timing, premixed gasoline percentage, and intake temperature. Comparisons were made to gasoline/diesel RCCI operation on the same engine platform at nominally the same operating condition.

We summarize results from comparative simulations of hybrid electric vehicles with either stoichiometric gasoline or diesel engines. Our simulations utilize previously published models of transient engine-out emissions and models of aftertreatment devices for both stoichiometric and lean exhaust. Fuel consumption and emissions were estimated for comparable gasoline and diesel light-duty hybrid electric vehicles operating over single and multiple urban drive cycles. Comparisons between the gasoline and diesel vehicle fuel consumptions and emissions were used to identify potential advantages and technical barriers for diesel hybrids.

The effect of biodiesel content on homogeneous charge compression ignition (HCCI) engine performance has been investigated both experimentally and by computer simulation. Combustion experiments were performed in a single cylinder HCCI engine using blends of soy biodiesel in ultra low sulfur diesel, with concentrations ranging from 0 to 50 vol% and equivalence ratios (Φ) from 0.38 to 0.48. Data from the engine tests included combustion analysis and exhaust composition analysis with standard gaseous emissions equipment. The engine utilized a custom port fuel injection strategy to provide highly premixed charges of fuel and air, making it possible to compare the results with single zone chemical kinetics simulations that were performed using CHEMKIN III, with a reaction set including 670 species and over 3000 reactions.

The compatibility of elastomeric materials used in fuel storage and dispensing applications was determined for test fuels representing neat gasoline and gasoline blends containing 10 and 17 vol.% ethanol, and 16 and 24 vol.% isobutanol. The actual test fuel chemistries were based on the aggressive formulations described in SAE J1681 for oxygenated gasoline. Elastomer specimens of fluorocarbon, fluorosilicone, acrylonitrile rubber (NBR), polyurethane, neoprene, styrene butadiene rubber (SBR) and silicone were exposed to the test fuels for 4 weeks at 60°C. After measuring the wetted volume and hardness, the specimens were dried for 20 hours at 60°C and then remeasured for volume and hardness. Dynamic mechanical analysis (DMA) was also performed to determine the glass transition temperature (Tg). Comparison to the original values showed that all elastomer materials experienced volume expansion and softening when wetted by the test fuels.

The compatibility of plastic materials used in gasoline storage and dispensing applications was determined for test fuels representing neat gasoline (Fuel C), and blends containing 25% ethanol (CE25a), 16% isobutanol (CiBu16a), and 24% isobutanol (CiBu24a). A solubility analysis was also performed and compared to the volume swell results obtained from the test fuel exposures. The plastic specimens were exposed to each test fuel for16 weeks at 60°C. After measuring the wetted volume and hardness, the specimens were dried for 65 hours at 60°C and then remeasured for volume and hardness. Dynamic mechanical analysis (DMA), which measures the storage modulus as a function of temperature, was also performed on the dried specimens to determine the temperature associated with the onset of the glass-to-rubber transition (Tg). For many of the plastic materials, the solubility analysis was able to predict the relative volume swell for each test fuel.

The compatibility of plastic materials used in fuel storage and dispensing applications was determined for an off-highway diesel fuel and a blend containing 20% bio-oil (Bio20) derived from a fast pyrolysis process. Bio20 is not to be confused with B20, which is a diesel blend containing 20% biodiesel. The feedstock, processing, and chemistry of biodiesel are markedly different from bio-oil. Plastic materials included those identified for use as seals, coatings, piping and fiberglass resins, but many are also used in vehicle fueling systems. The plastic specimens were exposed to the two fuel types for 16 weeks at 60°C. After measuring the wetted volume and hardness, the specimens were dried for 65 hours at 60°C and then remeasured to determine extent of property change. A solubility analysis was performed to better understand the performance of plastic materials in fuel blends composed of bio-oil and diesel.

The compatibility of plastic materials used in fuel storage and dispensing applications was determined for a test fuel representing gasoline blended with 10% ethanol. Prior investigations were performed on gasoline fuels containing 25, 50 and 85% ethanol, but the knowledge gap existing from 0 to 25% ethanol precluded accurate compatibility assessment of low level blends, especially for the current E10 fuel (gasoline containing 10% ethanol) used in most filling stations, and the recently accepted E15 fuel blend (gasoline blended with up to15% ethanol). For the majority of the plastic materials evaluated in this study, the wet volume swell (which is the parameter most commonly used to assess compatibility) was higher for fuels containing 25% ethanol, while the volume swell accompanying E10 was much lower.