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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.

With increasingly stringent regulations mandating the improvement of vehicle fuel economy, automotive manufacturers face growing pressure to develop and implement technologies that improve overall system efficiency. One such technology is an automatic (auto) stop-start feature. Auto stop-start reduces idle time and reduces fuel use by temporarily shutting the engine off when the vehicle comes to a stop and automatically re-starting it when the brake is released, or the accelerator is pressed. As mandated by the U.S. Congress, the U.S. Environmental Protection Agency (EPA) is required to keep the public informed about fuel saving practices. This is done, in partnership with the U.S. Department of Energy (DOE), through the fueleconomy.gov website. The “Fuel-Saving Technologies” and “Gas Mileage Tips” sections of the website are focused on helping the public make informed purchasing decisions and encouraging fuel-saving driving habits.

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 partnership for advancing combustion engines (PACE) is a US Department of Energy consortium involving multiple national laboratories and includes a goal of addressing key efficiency and emission barriers in light-duty engines fueled with a market-representative E10 gasoline. A major pillar of the initiative is the generation of detailed experimental data and modeling capabilities to understand and predict cold-start behavior. Cold-start, as defined by the time between first engine crank and three-way catalyst light-off, is responsible for a large percentage of NOx, unburned hydrocarbon and particulate matter emissions in light-duty engines. Minimizing emissions during cold-start is a trade-off between achieving faster light-off of the three-way catalyst and engine out emissions during that period.

In recent years there has been an increased interest in raising the octane level of gasoline to enable higher compression ratios (CR) in spark-ignition engines to improve vehicle fuel efficiency. A number of studies have examined opportunities to increase efficiency in future vehicles, but potential impacts on the legacy fleet have not received as much attention. This effort focused on experimental studies on an engine using high-octane fuels without changing the engine’s CR. Spark timing was advanced until maximum torque was reached or knock was encountered for each engine condition, using each individual fuel to maximize engine efficiency. Knock-limited conditions occurred as the output brake mean effective pressure (BMEP) neared the maximum attainable output at a given engine speed. Increasing research octane numbers generally enabled knock-free operation under a greater number of operating conditions.

Multimode engine operation uses two or more combustion modes to maximize engine efficiency across the operational range of a vehicle to achieve higher overall vehicle fuel economy than is possible with a single combustion mode. More specifically for this study, multimode solutions are explored that make use of boosted SI under high load operation and other advanced combustion modes such as advanced compression ignition (ACI) under part-load conditions to enable additional engine efficiency improvements across a broader range of the engine operating map. ACI combustion has well-documented potential to improve efficiency and emissions under part-load operation but poses challenges that limit full engine speed-load range. This study investigates the potential impact of ACI operational range on simulated fuel economy to help focus research on areas with the most opportunity for improving fuel economy.

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 fuel economy regulations increase in stringency, many manufacturers are implementing start-stop operation to enhance vehicle fuel economy. During start-stop operation, the engine shuts off when the vehicle is stationary for more than a few seconds. When the brake is released by the driver, the engine restarts. Depending on traffic conditions, start-stop operation can result in fuel savings from a few percent to close to 10%. Gasoline direct injection (GDI) engines are also increasingly available on light-duty vehicles. While GDI engines offer fuel economy advantages over port fuel injected (PFI) engines, they also tend to have higher PM emissions, particularly during start-up transients. Thus, there is interest in evaluating the effect of start-stop operation on PM emissions. In this study, a 2.5L GDI vehicle was operated over the FTP75 drive cycle.

Six blendstocks identified by the Co-Optimization of Fuels & Engines Program were used to prepare fuel blends using a fixed blendstock for oxygenate blending and a target RON of 97. The blendstocks included ethanol, n-propanol, isopropanol, isobutanol, diisobutylene, and a bioreformate surrogate. The blends were analyzed and used to establish interaction factors for a non-linear molar blending model that was used to predict RON and MON of volumetric blends of the blendstocks up to 35 vol%. Projections of efficiency increase, volumetric fuel economy increase, and tailpipe CO2 emissions decrease were produced using two different estimation techniques to evaluate the potential benefits of the blendstocks. Ethanol was projected to provide the greatest benefits in efficiency and tailpipe CO2 emissions, but at intermediate levels of volumetric fuel economy increase over a smaller range of blends than other blendstocks.

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.

A prototype three-way catalyst (TWC) with NOX storage component 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 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. Adding a NOX storage component to a TWC provides two benefits in the context of a passive SCR system: (1) enabling longer lean operation by storing NOX upstream and preserving NH3 inventory on the downstream SCR catalyst; and (2) increasing the quantity and rate of NH3 production during rich operation.

Today’s automotive industry is witnessing increasing applications of advanced high strength steels (AHSS) combined with innovative manufacturing techniques to satisfy fuel economy requirements of stringent environmental regulations. The integration of AHSS in novel automotive structure design has introduced huge advantages in mass reduction while maintaining their structural performances, yet several concerns have been raised for this relatively new family of steels. One of those concerns is their potentially high springback after forming, which can lead to geometrical deviation of the final product from its designed geometry and cause difficulties during assembly. From the perspective of accurate prediction, control and compensation of springback, further understanding on the effect of residual stress in AHSS parts is urged. In this work, the residual stress distribution in a 980GEN3 steel part after hydroforming is investigated via experimental and numerical approaches.

Reliable means for on-board detection of particulate filter failures or malfunctions are needed to meet diagnostics (OBD) requirements. Detecting these failures, which result in tailpipe particulate matter (PM) emissions exceeding the OBD limit, over all operating conditions is challenging. Current approaches employ differential pressure sensors and downstream PM sensors, in combination with particulate filter and engine-out soot models. These conventional monitors typically operate over narrowly-defined time windows and do not provide a direct measure of the filter’s state of health. In contrast, radio frequency (RF) sensors, which transmit a wireless signal through the filter substrate provide a direct means for interrogating the condition of the filter itself.

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.

The increasing use of diesel and gasoline particulate filters requires advanced on-board diagnostics (OBD) to prevent and detect filter failures and malfunctions. Early detection of upstream (engine-out) malfunctions is paramount to preventing irreversible damage to downstream aftertreatment system components. Such early detection can mitigate the failure of the particulate filter resulting in the escape of emissions exceeding permissible limits and extend the component life. However, despite best efforts at early detection and filter failure prevention, the OBD system must also be able to detect filter failures when they occur. In this study, radio frequency (RF) sensors were used to directly monitor the particulate filter state of health for both gasoline particulate filter (GPF) and diesel particulate filter (DPF) applications.

Greenhouse gas regulations and global economic growth are expected to drive a future demand shift towards diesel fuel in the transportation sector. This may create a market opportunity for cost-effective fuels in the light distillate range if they can be burned as efficiently and cleanly as diesel fuel. In this study, the emission performance of a low cetane number, low research octane number naphtha (CN 34, RON 56) was examined on a production 6-cylinder heavy-duty on-highway truck engine and aftertreatment system. Using only production hardware, both the engine-out and tailpipe emissions were examined during the heavy-duty emission testing cycles using naphtha and ultra-low-sulfur diesel (ULSD) fuels. Without any modifications to the hardware and software, the tailpipe emissions were comparable when using either naphtha or ULSD on the heavy duty test cycles.

Measuring axial exhaust species concentration distributions within a wall-flow aftertreatment device provides unique and significant insights regarding the performance of complex devices like the SCR-on-filter. In this particular study, a less complex aftertreatment configuration which includes a DOC followed by two uncoated partial flow filters (PFF) was used to demonstrate the potential and challenges. The PFF design in this study was a particulate filter with alternating open and plugged channels. A SpaciMS [1] instrument was used to measure the axial NO2 profiles within adjacent open and plugged channels of each filter element during an extended passive regeneration event using a full-scale engine and catalyst system. By estimating the mass flow through the open and plugged channels, the axial soot load profile history could be assessed.

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.

Deposit formation within turbocharger compressor housings can lead to compressor efficiency degradation. This loss of turbo efficiency may degrade fuel economy and increase CO2 and NOx emissions. To understand the role that engine oil composition and formulation play in deposit formation, five different lubricants were run in a fired engine test while monitoring turbocharger compressor efficiency over time. Base stock group, additive package, and viscosity modifier treat rate were varied in the lubricants tested. After each test was completed the turbocharger compressor cover and back plate deposits were characterized. A laboratory oil mist coking rig has also been constructed, which generated deposits having the same characteristics as those from the engine tests. By analyzing results from both lab and engine tests, correlations between deposit characteristics and their effect on compressor efficiency were observed.

For renewable fuels to displace petroleum, they must be compatible with emissions control devices. Pure biodiesel contains up to 5 ppm Na + K and 5 ppm Ca + Mg metals, which have the potential to degrade diesel emissions control systems. This study aims to address these concerns, identify deactivation mechanisms, and determine if a lower limit is needed. Accelerated aging of a production exhaust system was conducted on an engine test stand over 1001 h using 20% biodiesel blended into ultra-low sulfur diesel (B20) doped with 14 ppm Na. This Na level is equivalent to exposure to Na at the uppermost expected B100 value in a B20 blend for the system full-useful life. During the study, NOx emissions exceeded the engine certification limit of 0.33 g/bhp-hr before the 435,000-mile requirement.