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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.

In this work, a novel bearing test rig was used to evaluate the impact of oil viscoelasticity on friction torque and oil film thickness in a hydrodynamic journal bearing. The test rig used an electric motor to rotate a test journal, while a hydraulic actuator applied radial load to the connecting rod bearing. Lubrication of the journal bearing was accomplished via a series of axial and radial drillings in the test shaft and journal, replicating oil delivery in a conventional engine crankshaft. Journal bearing inserts from a commercial, medium duty diesel engine (Cummins ISB) were used. Oil film thickness was measured using high precision eddy current sensors. Oil film thickness measurements were taken at two locations, allowing for calculation of minimum oil film thickness. A high-precision, in-line torque meter was used to measure friction torque. Four test oils were prepared and evaluated.

This paper presents the evolution of a series of connected, automated vehicle technologies from simulation to in-vehicle validation for the purposes of minimizing the fuel usage of a class-8 heavy duty truck. The results reveal that an online, hierarchical model-predictive control scheme, implemented via the use of extended horizon driver advisories for velocity and gear, achieves fuel savings comparable to predictions from software-in-the-loop (SiL) simulations and engine-in-the-loop (EiL) studies that operated with a greater degree of powertrain and chassis automation. The work of this paper builds on prior work that presented in detail this predictive control scheme that successively optimizes vehicle routing, arrival and departure at signalized intersections, speed trajectory planning, platooning, predictive gear shifting, and engine demand torque shaping.

Wet clutch friction performance has historically been visualized by multiple graphs due to the number of temperatures and pressures required to characterize the system. However, this same friction performance can be visualized by a single graph using an alternative approach to map the friction data. Applying a method similar to that used to develop the Stribeck curve for journal bearings, a single system-level graph for wet clutches can be created. This paper will highlight how this visualization method, particularly when used to diagnose clutch failures, provides benefits in understanding the effects of both the friction material and the lubricant performance. We conducted extensive studies comparing ideal clutch systems with failed ones under a variety of conditions. Lubricant and friction material failures were independently studied, and durability tests were conducted to evaluate component failures.

In the last decade, numerous studies have been conducted to investigate the mechanism of Low Speed Pre-Ignition (LSPI) in Turbocharged Gasoline Direct Injection (TGDi) engines. According to technical reports, engine oil formulations can significantly influence the occurrence of LSPI particularly when higher levels of calcium-based additives are used, increasing the tendency for LSPI events to occur. While most of the studies conducted to date utilized engine tests, this paper evaluates the effect of engine oil formulations on LSPI under real-world driving conditions, so that not only the oil is naturally aged within an oil change interval, but also the vehicle is aged through total test distance of 160,000 km. Three engine oil formulations were prepared, and each tested in three vehicles leading to an identical fleet totaling nine vehicles, all of which were equipped with the same TGDi engine.

Increasingly stringent vehicle emissions legislation is being introduced throughout the world, regulating the allowed levels of particulate matter emitted from vehicle tailpipes. The regulation may prove challenging for gasoline vehicles equipped with modern gasoline direct injection (GDI) technology, owing to their increased levels of particulate matter production. It is expected that gasoline particulate filters (GPFs) will soon be fitted to most vehicles sold in China and Europe, allowing for carbonaceous particulate matter to be effectively captured. However, GPFs will also capture and accumulate non-combustible inorganic ash within them, mainly derived from engine oil. Studies exist to demonstrate the impact of such ash on GPF and vehicle performance, but these commonly make use of accelerated ash loading methods, which themselves introduce significant variation.

Downsized gasoline engines, coupled with gasoline direct injection (GDI) and turbocharging, have provided an effective means to meet both emissions standards and customers’ drivability expectations. As a result, these engines have become more and more common in the passenger vehicle marketplace over the past 10 years. To maximize fuel economy, these engines are commonly calibrated to operate at low speeds and high engine loads – well into the traditional ‘knock-limited’ region. Advanced engine controls and GDI have effectively suppressed knock and allowed the engines to operate in this high efficiency region more often than was historically possible. Unfortunately, many of these downsized, boosted engines have experienced a different type of uncontrolled combustion. This combustion occurs when the engine is operating under high load and low speed conditions and has been named Low Speed Pre-Ignition (LSPI). LSPI has shown to be very damaging to engine hardware.

Increasingly stringent fuel economy and emissions regulations around the world have forced the further optimization of nearly all vehicle systems. Many technologies exist to improve fuel economy; however, only a smaller sub-set are commercially feasible due to the cost of implementation. One system that can provide a small but significant improvement in fuel economy is the lubrication system of an internal combustion engine. Benefits in fuel economy may be realized by the reduction of engine oil viscosity and the addition of friction modifying additives. In both cases, advanced engine oils allow for a reduction of engine friction. Because of differences in engine design and architecture, some engines respond more to changes in oil viscosity or friction modification than others. For example, an engine that is designed for an SAE 0W-16 oil may experience an increase in fuel economy if an SAE 0W-8 is used.

This paper describes a novel design and verification process for analytical methods used in the development of advanced combustion strategies in internal combustion engines (ICE). The objective was to improve brake thermal efficiency (BTE) as part of the US Department of Energy SuperTruck program. The tools and methods herein discussed consider spray formation and injection schedule along with piston bowl design to optimize combustion efficiency, air utilization, heat transfer, emission, and BTE. The methodology uses a suite of tools to optimize engine performance, including 1D engine simulation, high-fidelity CFD, and lab-scale fluid mechanic experiments. First, a wide range of engine operating conditions are analyzed using 1-D engine simulations in GT Power to thoroughly define a baseline for the chosen advanced engine concept; secondly, an optimization and down-select step is completed where further improvements in engine geometries and spray configurations are considered.

One way to develop an understanding of soot formation and oxidation processes that occur during direct injection and combustion in an internal combustion engine is to image the natural luminosity from soot over time. Imaging is possible when there is optical access to the combustion chamber. After the images are acquired, the next challenge is to properly interpret the luminous distributions that have been captured on the images. A major focus of this paper is to provide guidance on interpretation of experimental images of soot luminosity by explaining how radiation from soot is predicted to change as it is transmitted through the combustion chamber and to the imaging. The interpretations are only limited by the scope of the models that have been developed for this purpose. The end-goal of imaging radiation from soot is to estimate the amount of soot that is present.

The mixing of a diesel spray with in-cylinder gases is driven by both turbulent mixing during the free-jet penetration phase and by mixing during the jet’s impingement on surfaces such as the piston bowl. Current reduced order models, and many experiments, focus solely on the free-jet penetration phase, although jet-wall interaction occurs during a significant portion of the duration of a fuel injection in both small-bore and large-bore engines. A control volume-based model for the spreading of an impinging spray along a flat wall is presented as a first step towards capturing key jet processes during the impingement phase of fuel injection. Schlieren measurements of impinging gaseous jets are used to evaluate the model.

The growing need for improved fuel economy is a global challenge due to continuously tightening environmental regulations targeting lower CO2 emission levels via reduced fuel consumption in vehicles. In order to reach these fuel efficiency targets, it necessitates improvements in vehicle transmission hardware components by applying advanced technologies in design, materials and surface treatments etc., as well as matching lubricant formulations with appropriate additive chemistry. Axle lubricants have a considerable impact on fuel economy. More importantly, they can be tailored to deliver maximum operational efficiency over specific or wide ranges of operating conditions. The proper lubricant technology with well-balanced chemistries can simultaneously realize both fuel economy and hardware protection, which are perceived to have a trade-off relationship.

The operating conditions of a typical motorcycle are considerably different than those of a typical passenger car and thus require an oil capable of handling the unique demands. One primary difference, wet clutch lubrication, is already addressed by the current JASO four-stroke motorcycle engine oil specification (JASO T 903:2011). Another challenge for the oil is gear box lubrication, which may be addressed in part with the addition of a gear protection test in a future revision to the JASO specification. A third major difference between a motorcycle oil and passenger car oil is the more severe conditions an oil is subjected to within a motorcycle engine, due to higher temperatures, engine speeds and power densities. Scooters, utilizing a transmission not lubricated by the crankcase oil, also place higher demands on an engine oil, once again due to higher temperatures, engine speeds and power densities.

This paper presents simple but comprehensive modeling of the loads on the rubber sandwich-type mounts that often suspend the drum(s) in vibratory compactors or asphalt rollers. The goal of the modeling is to predict the overall performance of the rubber mount system. The modeling includes calculations to 1) identify and quantify all predictable low-frequency loads on the rubber mounts during normal vehicle operations, 2) predict the steady-state high-frequency vibration response of the drum, rubber mounts, and vehicle frame during compaction operations, 3) predict the heat generation in the rubber mounts from their hysteretic damping, and 4) predict the fatigue life and life distribution of the rubber mounts. Some typical results of the modeling are provided along with some brief criteria to assess suspension performance. Other, unpredictable suspension loads are discussed but not modeled.

This paper is part of a larger body of experimental and computational work devoted to studying the role of close-coupled post injections on soot reduction in a heavy-duty optical engine. It is a continuation of an earlier computational paper. The goals of the current work are to develop new CFD analysis tools and methods and apply them to gain a more in depth understanding of the different in-cylinder environments into which fuel from main- and post-injections are injected and to study how the in-cylinder flow, thermal and chemical fields are transformed between start of injection timings. The engine represented in this computational study is a single-cylinder, direct-injection, heavy-duty, low-swirl engine with optical components. It is based on the Cummins N14, has a cylindrical shaped piston bowl and an eight-hole injector that are both centered on the cylinder axis. The fuel used was n-heptane and the engine operating condition was light load at 1200 RPM.

The beneficial effects of contact disruption in modulation-assisted machining of aerospace alloys have been well documented, but sources for such improvements are not well understood. This study explores the underlying nature of differences that occur in energy dissipation during conventional and modulation-assisted machining by characterizing the relationship between controllable process parameters and their effects on chip formation. Simultaneous in situ force and tool position measurements are used to show that the forces in modulation-assisted machining can be described by empirical force models in conventional machining conditions. These models are found to accurately describe plastic dissipation over a range of modulation conditions and configurations, including in cases where energy expenditure decreases with the application of modulation. These observations suggest that the underlying response in modulation-assisted machining is analogous to that of conventional machining.

This paper illustrates a method to determine the experimental uncertainties in the measurement of tailpipe emissions of carbon dioxide, carbon monoxide, nitrogen oxides, hydrocarbons, and particulates of medium-, and heavy-duty vehicles when tested on a heavy-duty chassis dynamometer and full-scale dilution tunnel. Tests are performed for different chassis dynamometer driving cycles intended to simulate a wide range of operating conditions. Vehicle exhaust is diluted in the dilution tunnel by mixing with conditioned air. Samples are drawn through probes for raw exhaust, diluted exhaust and particulates and measured using laboratory grade emission analyzers and a microbalance. At the end of a driving cycle, results are reported for the above emissions in grams/mile for raw continuous, dilute continuous, dilute bag, and particulate measurements.

The Pennsylvania State University Advanced Vehicle Team (PSUAVT) is one of sixteen collegiate teams across North America participating in the EcoCAR 2: “Plugging In to the Future” competition. The PSUAVT designed and implemented a series plug-in hybrid electric vehicle (PHEV) for this competition. This architecture allows the vehicle to operate as a pure electric vehicle until the energy storage system (ESS) state of charge (SOC) is depleted. The auxiliary power unit (APU) then supplements the battery to extend range beyond that of a purely electric vehicle. To implement this design concept, the PSUAVT re-engineered a General Motors (GM) donated 2013 Chevrolet Malibu to house an electric traction motor, high capacity lithium-ion battery pack, and APU consisting of a low-displacement engine fueled by 85% ethanol/15% gasoline (E85) mixture and an electric generator.

Mn and/or rare earth-doped xCaTiO₃ - (1-x)CaMeO₃ dielectrics, where Me=Hf or Zr and x=0.7, 0.8, and 0.9 were developed to yield materials with room temperature relative permittivities of Εr ~ 150-170, thermal coefficients of capacitance (TCC) of ± 15.8% to ± 16.4% from -50 to 150°C, and band gaps of ~ 3.3-3.6 eV as determined by UV-Vis spectroscopy. Un-doped single layer capacitors exhibited room temperature energy densities as large as 9.0 J/cm₃, but showed a drastic decrease in energy density above 100°C. When doped with 0.5 mol% Mn, the temperature dependence of the breakdown strength was minimized, and energy densities similar to room temperature values (9.5 J/cm₃) were observed up to 200°C. At 300°C, energy densities as large as 6.5 J/cm₃ were measured. These observations suggest that with further reductions in grain size and dielectric layer thickness, the xCaTiO₃ - (1-x)CaMeO₃ system is a strong candidate for integration into future power electronics applications.

Deep-hole drilling is among the most critical precision machining processes for production of high-performance discrete components. The effects of drilling with superimposed, controlled low-frequency modulation - Modulation-Assisted Machining (MAM) - on the surface textures created in deep-hole drilling (ie, gun-drilling) are discussed. In MAM, the oscillation of the drill tool creates unique surface textures by altering the burnishing action typical in conventional drilling. The effects of modulation frequency and amplitude are investigated using a modulation device for single-flute gun-drilling on a computer-controlled lathe. The experimental results for the gun-drilling of titanium alloy with modulation are compared and contrasted with conventional gun-drilling. The chip morphology and surface textures are characterized over a range of modulation conditions, and a model for predicting the surface texture is presented. Implications for production gun-drilling are discussed.