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Gasoline direct injection (GDI) engines can offer improved fuel economy and higher performance over their port fuel-injected (PFI) counterparts, and are now appearing in increasingly more U.S. and European vehicles. Small displacement, turbocharged GDI engines are replacing large displacement engines, particularly in light-duty trucks and sport utility vehicles, in order for manufacturers to meet more stringent fuel economy standards. GDI engines typically emit the most particulate matter (PM) during periods of rich operation such as start-up and acceleration, and emissions of air toxics are also more likely during this condition. A 2.0 L GDI engine was operated at lambda of 0.91 at typical loads for acceleration (2600 rpm, 8 bar BMEP) on three different fuels; an 87 anti-knock index (AKI) gasoline (E0), 30% ethanol blended with the 87 AKI fuel (E30), and 48% isobutanol blended with the 87 AKI fuel.

Thermoelectric generators (TEGs) have been researched and developed for harvesting energy from otherwise wasted heat. For automotive applications this will most likely involve using internal combustion engine exhaust as the heat source, with the TEG positioned after the catalyst system. Applications to exhaust gas recirculation systems and compressed air coolers have also been suggested. A thermoelectric generator based on half-Heusler thermoelectric materials was developed, engineered, and fabricated, targeting a gasoline passenger sedan application. This generator was installed on a gasoline engine exhaust system in a dynamometer cell, and positioned immediately downstream of the close-coupled three-way catalyst. The generator was characterized using a matrix of steady-state conditions representing the important portions of the engine map. Detailed performance results are presented.

Proper maintenance can help vehicles perform as designed, positively affecting fuel economy, emissions, and the overall drivability. This effort investigates the effect of one maintenance factor, intake air filter replacement, with primary focus on vehicle fuel economy, but also examining emissions and performance. Older studies, dealing with carbureted gasoline vehicles, have indicated that replacing a clogged or dirty air filter can improve vehicle fuel economy and conversely that a dirty air filter can be significantly detrimental to fuel economy. The effect of clogged air filters on the fuel economy, acceleration and emissions of five gasoline fueled vehicles is examined. Four of these were modern vehicles, featuring closed-loop control and ranging in model year from 2003 to 2007. Three vehicles were powered by naturally aspirated, port fuel injection (PFI) engines of differing size and cylinder configuration: an inline 4, a V6 and a V8.

Tests were conducted during 2008 on 16 late-model, conventional vehicles (1999 through 2007) to determine short-term effects of mid-level ethanol blends on performance and emissions. Vehicle odometer readings ranged from 10,000 to 100,000 miles, and all vehicles conformed to federal emissions requirements for their federal certification level. The LA92 drive cycle, also known as the Unified Cycle, was used for testing as it was considered to more accurately represent real-world acceleration rates and speeds than the Federal Test Procedure (FTP) used for emissions certification testing. Test fuels were splash-blends of up to 20 volume percent ethanol with federal certification gasoline. Both regulated and unregulated air-toxic emissions were measured. For the aggregate 16-vehicle fleet, increasing ethanol content resulted in reductions in average composite emissions of both NMHC and CO and increases in average emissions of ethanol and aldehydes.

Proper maintenance can help vehicles perform as designed, positively affecting fuel economy, emissions, and overall driveability. This paper addresses the issue of whether air filter replacement improves fuel economy. Described are measured results for increasing air filter pressure drop in turbocharged diesel-engine-powered vehicles, with primary focus on changes in vehicle fuel economy but also including emissions and performance. Older studies of carbureted gasoline vehicles have indicated that replacing a clogged or dirty air filter can improve vehicle fuel economy and, conversely, that a dirty air filter can be significantly detrimental to fuel economy. In contrast, a recent study showed that the fuel economy of modern gasoline vehicles is virtually unaffected by filter clogging due to the closed loop control and throttled operation of these engines. Because modern diesel engines operate without throttling (or with minimal throttling), a different result could be anticipated.

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.

The U.S. Department of Energy’s Co-Optimization of Fuels and Engines initiative (Co-Optima) aims to simultaneously transform both transportation fuels and engines to maximize performance and energy efficiency. Researchers from across the DOE national laboratories are working within Co-Optima to develop merit functions for evaluating the impact of fuel formulations on the performance of advanced engines. The merit functions relate overall engine efficiency to specific measurable fuel properties and will serve as key tools in the fuel/engine co-optimization process. This work focused on developing a term for the Co-Optima light-duty boosted spark ignition (SI) engine merit function that captures the effects of fuel composition on emissions control system performance. For stoichiometric light-duty SI engines, the majority of NOx, NMOG, and CO emissions occur during cold start, before the three-way catalyst (TWC) has reached its “light-off” temperature.

This work explores the impact of the interaction of lubricant and fuel properties on the propensity for stochastic pre-ignition (SPI). Findings are based on statistically significant changes in SPI tendency and magnitude, as determined by measurements of cylinder pressure. Specifically, lubricant detergents, lubricant volatility, fuel volatility, fuel chemical composition, fuel-wall impingement, and engine load were varied to study the physical and chemical effects of fuel-lubricant interactions on SPI tendency. The work illustrates that at low loads, with fuels susceptible to SPI events, lubricant detergent package effects on SPI were non-significant. However, with changes to fuel distillation, fuel-wall impingement, and most importantly engine load, lubricant detergent effects could be observed even at reduced loads This suggests that there is a thermal effect associated with the higher load operation.

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.

Prior research studies have investigated a wide variety of gasoline compression ignition (GCI) injection strategies and the resulting fuel stratification levels to maintain control over the combustion phasing, duration, and heat release rate. Previous GCI research at the US Department of Energy’s Oak Ridge National Laboratory has shown that for a combustion mode with a low degree of fuel stratification, called “partial fuel stratification” (PFS), gasoline range fuels with anti-knock index values in the range of regular-grade gasoline (~87 anti-knock index or higher) provides very little controllability over the timing of combustion without significant boost pressures. On the contrary, heavy fuel stratification (HFS) provides control over combustion phasing but has challenges achieving low temperature combustion operation, which has the benefits of low NOX and soot emissions, because of the air handling burdens associated with the required high exhaust gas recirculation rates.

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.

Aggressive driving is an important topic for many reasons, one of which is higher energy used per unit distance traveled, potentially accompanied by an elevated production of greenhouse gases and other pollutants. Examining a large data set of self-reported fuel economy (FE) values revealed that the dispersion of FE values is quite large and is larger for hybrid electric vehicles (HEVs) than for conventional gasoline vehicles. This occurred despite the fact that the city and highway FE ratings for HEVs are generally much closer in value than for conventional gasoline vehicles. A study was undertaken to better understand this and better quantify the effects of aggressive driving, including reviewing past aggressive driving studies, developing and exercising a new vehicle energy model, and conducting a related experimental investigation.

This work explores the dependence of fuel ignition delay on stochastic pre-ignition (SPI). Findings are based on bulk gas thermodynamic state, where the effects of kinetically controlled bulk gas pre-spark heat release (PSHR) are correlated to SPI tendency and magnitude. Specifically, residual gas and low temperature PSHR chemistry effects and observations are explored, which are found to be indicative of bulk gas conditions required for strong SPI events. Analyzed events range from non-knocking SPI to knocking SPI and even detonation SPI events in excess of 325 bar peak cylinder pressure. The work illustrates that singular SPI event count and magnitude are found to be proportional to PSHR of the bulk gas mixture and residual gas fraction. Cycle-to-cycle variability in trapped residual mass and temperature are found to impose variability in singular SPI event count and magnitude.

The three foundational elements that determine mobile source energy use and tailpipe carbon dioxide (CO2) emissions are the tractive energy requirements of the vehicle, the energy conversion efficiency of the propulsion system, and the energy source. The tractive energy requirements are determined by the vehicle's mass, aerodynamic drag, tire rolling resistance, and parasitic drag. The energy conversion efficiency of the propulsion system is dictated by the tractive efficiency, non-tractive energy use, kinetic energy recovery, and parasitic losses. The energy source determines the mobile source CO2 emissions. For current vehicles, tractive energy requirements and overall energy conversion efficiency are readily available from the decomposition of test data. For future applications, plausible levels of mass reduction, aerodynamic drag improvements, and tire rolling resistance can be transposed into the tractive energy domain.