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RADIATION can produce almost instantaneous failure of modern aircraft lubricants, tests at Southwest Research Institute show. Two types of failures demonstrated are rapid viscosity rise and loss of heat conductivity. Furthermore, it was found that lubricants can become excessively corrosive under high-level radiation. Generally speaking, the better lubricants appeared to improve in performance while marginal ones deteriorated to a greater extent under radiation. When the better lubricants were subjected to static irradiation prior to the deposition test, there was a minor increase in deposition number as the total dose was increased.

As Electric and Hybrid Electric Vehicles (EVs and HEVs) become more prevalent, there is a need to change the power source from gasoline on the vehicle to electricity from the grid in order to mitigate requirements for onboard energy storage (battery weight) as well as to reduce dependency on oil by increasing dependency on the grid (our coal, gas, and renewable energy instead of their oil). Traditional systems for trains and buses rely on physical contact to transfer electrical energy to vehicles in motion. Until recently, conventional magnetically coupled systems required a gap of less than a centimeter. This is not practical for vehicles of the future.

The question of whether increasing the fuel economy of light-duty natural gas fueled vehicles can improve their economic competitiveness in the U.S. market, and help the US Department of Energy meet stated goals for such vehicles is explored. Key trade-offs concerning costs, exhaust emissions and other issues are presented for a number of possible advanced engine designs. Projections of fuel economy improvements for a wide range of lean-burn engine technologies have been developed. It appears that compression ignition technologies can give the best potential fuel economy, but are less competitive for light-duty vehicles due to high engine cost. Lean-burn spark ignition technologies are more applicable to light-duty vehicles due to lower overall cost. Meeting Ultra-Low Emission Vehicle standards with efficient lean-burn natural gas engines is a key challenge.

A METHOD is described in this paper by which the rates of gear wear under different conditions can be determined by the use of the radioactive tracer technique. With this method one can measure the minutest amount of wear at loads and speeds much below critical destructive conditions. This method makes possible the continuous determination of rates of gear wear at all loads and speeds in actual full-scale units. In this investigation, the radioactive tracer technique has been used to determine the rates of gear wear when using a straight mineral oil and when using an extreme-pressure gear lubricant.

Dedicated Exhaust Gas Recirculation (D-EGR®) technology provides a novel means for fuel efficiency improvement through efficient, on-board generation of H2 and CO reformate [1, 2]. In the simplest form of the D-EGR configuration, reformate is produced in-cylinder through rich combustion of the gasoline-air charge mixture. It is also possible to produce more H2 by means of a Water Gas Shift (WGS) catalyst, thereby resulting in further combustion improvements and overall fuel consumption reduction. In industrial applications, the WGS reaction has been used successfully for many years. Previous engine applications of this technology, however, have only proven successful to a limited degree. The motivation for this work was to develop and optimize a WGS catalyst which can be employed to a D-EGR configuration of an internal combustion engine. This study consists of two parts.

Water injection (WI) can improve gasoline engine performance and efficiency, and on-board water recovery technology could eliminate the need for customers to refill an on-board water reservoir. In this regard, the technical feasibility of exhaust water recovery (EWR) is described in this paper. Water injection testing was conducted at a full load condition (5000 rpm/18.1 bar BMEP) and a high load condition (3000 rpm/14.0 bar BMEP) on a turbocharged gasoline direction injection (GTDI) engine. Water recovery testing was conducted both after the exhaust gas recirculation (EGR) cooler and after the charge air cooler (CAC) at a high load (3000 rpm/14.0 bar BMEP), as well as a part load (2080 rpm/6.8 bar BMEP) condition, at temperatures ca. 10-15 °C below the dew point of the flow stream. Three types of water separation designs were tested: a passive cyclone separator (CS), a passive membrane separator (MEM), and an active separator (AS).

This paper presents a simple method of using Voronoi partitions for estimating vehicle fuel economy from a limited set of engine operating conditions. While one of the overarching goals of engine research is to continually improve vehicle fuel economy, evaluating the impact of a change in engine operating efficiency on the resulting fuel economy is a non-trivial task and typically requires drive cycle simulations with experimental data or engine model predictions and a full suite of engine controllers over a wide range of engine speeds and loads. To avoid the cost of collecting such extensive data, proprietary methods exist to estimate fuel economy from a limited set of engine operating conditions. This study demonstrates the use of Voronoi partitions to cluster and quantize the fuel consumed along a complex trajectory in speed and load to generate fuel consumption estimates based on limited simulation or experimental results.

The objectives of this project were to investigate the corrosivity of condensate in a stoichiometric spark-ignited (SI) engine when running exhaust gas recirculation (EGR) and to determine the effects of sulfur-in-fuel on corrosion. A 2.0 L turbocharged direct-injected SI engine was operated with low-pressure EGR for this study. The engine was instrumented for visual, thermodynamic, and electrochemical analyses to determine the potential for corrosion at locations where condensation was deemed likely in a low-pressure loop EGR (LPL-EGR) engine. The electrochemical analysis was performed using multi-electrode array (MEA) corrosion probes. Condensate was also collected and analyzed. These analyses were performed downstream of both the charge air cooler (CAC) and the EGR cooler. It was found that while conditions existed for sulfuric acid to form with high-sulfur fuel, no sulfuric acid was detected by any of the measurement methods.

Tremendous amount of useful information can be extracted from the cylinder pressure signal for engine combustion control. However, the physical cylinder pressure sensors are undesirably expensive and their health need to be monitored for fault diagnostic purpose as well. This paper presents the results of the development of a virtual cylinder pressure sensor (VCPS) with individual variable-oriented independent estimators. Two neural network-based independent cylinder pressure related variable estimators were developed and verified at steady state. The results show that these models can predict the variables correctly compared with the extracted variables from the measured physical cylinder pressure sensor signal. Good generalization capabilities of the developed models are observed in the sense that the models work well not only for the training data set but also for the new inputs that they have never been exposed to before.

A 28-vehicle fleet test was executed to verify and quantify the NOX emissions reductions achieved through the use of Infineum's Vektron 6913 gasoline additive. The fleet composition and experimental design were finalized in collaborative discussions with US Environmental Protection Agency (EPA) Office of Transportation & Air Quality (OTAQ) and consultation / advice from several major US automotive manufacturers. The test was conducted over a period of five months at Southwest Research Institute. Statistical analysis of the emissions data indicated a 10% average fleet reduction in NOX emissions without any negative impact on other criteria pollutants (CO, HC) or fuel economy.

An optimal energy management strategy (Optimal EMS) can yield significant fuel economy (FE) improvements without vehicle velocity modifications. Thus it has been the subject of numerous research studies spanning decades. One of the most challenging aspects of an Optimal EMS is that FE gains are typically directly related to high fidelity predictions of future vehicle operation. In this research, a comprehensive dataset is exploited which includes internal data (CAN bus) and external data (radar information and V2V) gathered over numerous instances of two highway drive cycles and one urban/highway mixed drive cycle. This dataset is used to derive a prediction model for vehicle velocity for the next 10 seconds, which is a range which has a significant FE improvement potential. This achieved 10 second vehicle velocity prediction is then compared to perfect full drive cycle prediction, perfect 10 second prediction.

There is a pressing need to develop accurate and robust approaches for predicting vehicle speed to enhance fuel economy/energy efficiency, drivability and safety of automotive vehicles. This paper details outcomes of research into various methods for the prediction of vehicle velocity. The focus is on short-term predictions over 1 to 10 second prediction horizon. Such short-term predictions can be integrated into a hybrid electric vehicle energy management strategy and have the potential to improve HEV energy efficiency. Several deterministic and stochastic models are considered in this paper for prediction of future vehicle velocity. Deterministic models include an Auto-Regressive Moving Average (ARMA) model, a Nonlinear Auto-Regressive with eXternal input (NARX) shallow neural network and a Long Short-Term Memory (LSTM) deep neural network. Stochastic models include a Markov Chain (MC) model and a Conditional Linear Gaussian (CLG) model.

Accurate perception of the driving environment and a highly accurate position of the vehicle are paramount to safe Autonomous Vehicle (AV) operation. AVs gather data about the environment using various sensors. For a robust perception and localization system, incoming data from multiple sensors is usually fused together using advanced computational algorithms, which historically requires a high-compute load. To reduce AV compute load and its negative effects on vehicle energy efficiency, we propose a new infrastructure information source (IIS) to provide environmental data to the AV. The new energy–efficient IIS, chip–enabled raised pavement markers are mounted along road lane lines and are able to communicate a unique identifier and their global navigation satellite system position to the AV. This new IIS is incorporated into an energy efficient sensor fusion strategy that combines its information with that from traditional sensor.

A major driving force for change in light-duty vehicle design and technology is the National Highway Traffic Safety Administration (NHTSA) and the U.S. Environmental Protection Agency (EPA) joint final rules concerning Corporate Average Fuel Economy (CAFE) and greenhouse gas (GHG) emissions for model years 2017 (MY17) through 2025 (MY25) passenger cars and light trucks. The chief goal of this current study is to compare the already rapid pace of fuel economy improvement and technological change over the previous decade to the required rate of change to meet regulations over the next decade. EPA and NHTSA comparisons of the model year 2005 (MY05) US light-duty vehicle fleet to the model year 2015 (MY15) fleet shows improved fuel economy (FE) of approximately 26% using the same FE estimating method mandated for CAFE regulations. Future predictions by EPA and NHTSA concerning ensemble fleet fuel economy are examined as an indicator of required vehicle rate-of-change.

The confluence of fuel economy improvement requirements and increased use of ethanol as a gasoline blend component has led to various studies into the efficiency and performance benefits to be had when using high octane number, high ethanol content fuels in modern engines. As part of a comprehensive study of the autoignition of fuels in both the CFR octane rating engine and a modern, direct injection, turbocharged spark ignited engine, a series of fuel blends were prepared with market relevant ranges of octane numbers and ethanol blends levels. The paper reports on the first part of this study where fuel flow measurements were done on a single cylinder research engine, utilizing a GM LHU combustion system, and then used to predict drive cycle fuel economy. For a range of engine speeds and manifold air pressures, spark timing was adjusted to achieve either the maximum brake torque (MBT) or a matched 50 % mass fraction burnt location.

Vegetable oils are candidates for alternative fuels in diesel engines. These oils, such as soybean, sunflower, rapeseed, cottonseed, and peanut, consist of various triglycerides. The chemistry of the degradation of vegetable oils when used as alternate diesel fuels thus corresponds to that of triglycerides. To study the chemistry occurring during the precombustion phase of a vegetable oil injected into a diesel engine, a reactor simulating a diesel engine was constructed. Pure triglycerides were injected into the reactor in order to determine differences in the precombustion behavior of the various triglycerides. The reactor allowed motion pictures to be prepared of the injection event as the important reaction parameters, such as pressure, temperature, and atmosphere were varied. Furthermore, samples of the degradation products of precombusted triglycerides were collected and analyzed (gas chromatography / mass spectrometry).

Growing environmental concerns and stringent vehicle emissions regulations has created an urge in the automotive industry to move towards electrified propulsion systems. Reducing and eliminating the emission from public transportation vehicles plays a major role in contributing towards lowering the emission level. Battery electric buses are regarded as a type of promising green mass transportation as they provide the advantage of less greenhouse gas emissions per passenger. However, the electric bus faces a problem of limited range and is not able to drive throughout the day without being recharged. This research studies a public bus transit system example which servicing the city of Ann Arbor in Michigan and investigates the impact of different electrification levels on the final CO2 reduction. Utilizing models of a conventional diesel, hybrid electric, and battery electric bus, the CO2 emission for each type of transportation bus is estimated.

The Energy Finite Element Analysis(EFEA) is a recent development for high frequency vibro-acoustic analysis, and constitutes an evolution in the area of high frequency computations. The EFEA is a wave based approach, while the SEA is a modal based approach. In this paper the similarities in the theoretical development of the two methods are outlined. The main scope of this paper is to establish the validity of the EFEA by analyzing several complex structural-acoustic systems. The EFEA solutions are compared successfully to SEA results and to solutions obtained from extremely dense conventional FEA models.

Reactivity Controlled Compression Ignition (RCCI) natural gas/diesel dual-fuel combustion has been shown to achieve high thermal efficiency with low NOX and PM emissions, but has traditionally been limited to low to medium loads. High BMEP operation typically requires high substitution rates (i.e., >90% NG), which can lead to high cylinder pressure, pressure rise rates, knock, and combustion loss. In previous studies, compression ratio was decreased to achieve higher load operation, but thermal efficiency was sacrificed. For this study, a multi-cylinder heavy-duty engine that has been modified for dual-fuel operation (diesel direct-injection and natural gas (NG) fumigated into the intake stream) was used to explore RCCI and other dual-fuel combustion modes at high compression ratio, while maintaining stock lug curve capability (i.e., extending dual-fuel operation to high loads where conventional diesel combustion traditionally had to be used).

This paper describes experiments conducted to determine the regulated emissions, ozone-forming potentials, specific reactivities, and reactivity adjustment factors for eight butane and propane alternative fuel blends run on a light-duty vehicle, emission certified to be a California transitional low emission vehicle (TLEV) and converted to operate on liquefied petroleum gas (LPG). Duplicate EPA FTP emission tests were conducted with each fuel. Hydrocarbon speciation was utilized to determine reactivity-adjusted non-methane organic gases (NMOG) emissions for one test on each fuel. Results showed that all eight fuels could allow the converted vehicle to pass California ultra-low emission vehicle (ULEV) NMOG and oxides of nitrogen (NOx) standards. Six of the eight fuels could allow the vehicle to pass ULEV carbon monoxide (CO) standards. BUTANE has been an important gasoline blending component for many years.