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Φ-sensitivity is a fuel characteristic that has important benefits for the operation and control of low-temperature gasoline combustion (LTGC) engines. A fuel is φ-sensitive if its autoignition reactivity varies with the fuel/air equivalence ratio (φ). Thus, multiple-injection strategies can be used to create a φ-distribution that leads to several benefits. First, the φ-distribution causes a sequential autoignition that reduces the maximum heat release rate. This allows higher loads without knock and/or advanced combustion timing for higher efficiencies. Second, combustion phasing can be controlled by adjusting the fuel-injection strategy. Finally, experiments show that intermediate-temperature heat release (ITHR) increases with φ-sensitivity, increasing the allowable combustion retard and improving stability. A detailed mechanism was applied using CHEMKIN to understand the chemistry responsible for φ-sensitivity.

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.

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.

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.

CFD (Computational Fluid Dynamics) has been used to analyze vehicle air flow. In cross wind conditions an asymmetrical flow field around the vehicle is present. Under these circumstances, in addition to the forces present with symmetric air flow (drag and lift forces and pitching moment), side forces and moments (rolling and yawing) occur. Issues related to fuel economy, driveability, sealing effects (caused by suction exerted on the door), structural integrity (sun roof, spoiler), water management (rain deposit), and dirt deposit (shear stress) have been investigated. Due to the software developments and computer hardware improvements, results can be obtained within a reasonable time frame with excellent accuracy (both geometry and analytical solution). The flow velocity, streamlines, pressure field, and component forces can be extracted from the analysis results through visualization to identify potential improvement areas.

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.

THIS paper describes what the authors consider to be a simplified method of determining the vapor-locking tendencies of gasolines. The study of vapor lock was undertaken after they found the Reid vapor pressure method to be inadequate. The result of their work was the development of the General Motors vapor pressure, a single number which predicts vapor-locking tendency. The authors point out the following advantages of the new method: It allows direct comparisons of vapor-lock test results of different reference fuel systems; establishes distribution curves of volatility requirements of cars for vapor-lock free operation and of vapor-locking tendencies of gasolines; is a common reference value for both petroleum and automotive engineers. Finally, it more realistically evaluates the effects of small weathering losses on vapor-locking tendency than does Rvp.

Exhaust gas recirculation (EGR) can be used to mitigate knock in SI engines. However, experiments have shown that the effectiveness of various EGR constituents to suppress knock varies with fuel type and compression ratio (CR). To understand some of the underlying mechanisms by which fuel composition, octane sensitivity (S), and CR affect the knock-mitigation effectiveness of EGR constituents, the current paper presents results from a chemical-kinetics modeling study. The numerical study was conducted with CHEMKIN, imposing experimentally acquired pressure traces on a closed reactor model. Simulated conditions include combinations of three RON-98 (Research Octane Number) fuels with two octane sensitivities and distinctive compositions, three EGR diluents, and two CRs (12:1 and 10:1). The experimental results point to the important role of thermal stratification in the end-gas to smooth peak heat-release rate (HRR) and prevent acoustic noise.

The objectives of this paper are to describe the research efforts in diesel engine combustion at Sandia National Laboratories' Combustion Research Facility and to provide recent experimental results. We have four diesel engine experiments supported by the Department of Energy, Office of Heavy Vehicle Technologies: a one-cylinder version of a Cummins heavy-duty engine, a diesel simulation facility, a one-cylinder Caterpillar engine to evaluate combustion of alternative fuels, and a homogeneous-charge, compression-ignition (HCCI) engine. Recent experimental results of diesel combustion research will be discussed and a description will be given of our HCCI experimental program and of our HCCI modeling work.

The emission of excessive quantities of NOx when the automobile air conditioner is turned on has received a fair amount of attention in recent years. Since NOx is a smog precursor, it is important to understand the reasons for this jump in emissions especially on hot sunny days when air conditioner usage is at a maximum. A simple thermodynamic model is used to demonstrate how the torque from a typical air conditioner compressor is mainly related to the ambient temperature. The compressor's on-off cycling patterns are also characterized. Since the compressor significantly loads the engine, it affects fuel economy and emissions. The key independent variable that we employ to represent engine load is fuel rate. The correlations between engine-out NOx emissions and fuel rate are shown for a number of light duty vehicles and trucks. From these, a physical model for engine-out NOx emissions (with and without air conditioning) is presented.

To cope with regulatory standards, minimizing tailpipe emissions with rapid catalyst light-off during cold-start is critical. This requires catalyst-heating operation with increased exhaust enthalpy, typically by using late post injections for retarded combustion and, therefore, increased exhaust temperature. However, retardability of post injection(s) is constrained by acceptable pollutant emissions such as unburned hydrocarbon (UHC). This study provides further insight into the mechanisms that control the formation of UHC under catalyst-heating operation in a medium-duty diesel engine, and based on the understanding, develops combustion strategies to simultaneously improve exhaust enthalpy and reduce harmful emissions. Experiments were performed with a full boiling-range diesel fuel (cetane number of 45) using an optimized five-injections strategy (2 pilots, 1 main, and 2 posts) as baseline condition.

In this paper the development of statistical metamodels and statistical fast running models is presented first. They are utilized for propagating uncertainties in a multi-discipline design optimization process. Two main types of uncertainty can be considered in this manner: uncertainty due to variability in design variables or in random parameters; uncertainty due to the utilization of metamodels instead of the actual simulation models during the optimization process. The value of the new developments and their engagement in multi-discipline design optimization is demonstrated through a case study. An underwater vehicle is designed under four different disciplines, namely, noise radiation, self-noise due to TBL excitation, dynamic response due to propulsion impact loads, and response to an underwater detonation.

Wet clutch packs are widely used in today’s automatic transmission systems for gear-ratio shifting. The frictional interfaces between the clutch plates are continuously lubricated with transmission fluid for both thermal and friction management. The open clutch packs shear transmission fluid across the rotating plates, contributing to measurable energy losses. A typical multi-speed transmission includes as many as 5 clutch packs. Of those, two to three clutches are open at any time during a typical drive cycle, presenting an opportunity for fuel economy gain. However, reducing open clutch drag is very challenging, while meeting cooling requirements and shift quality targets. In practice, clutch design adjustment is performed through trial-and-error evaluation of hardware on a test bench. The use of analytical methodologies is limited for optimizing clutch design features due to the complexity of fluid-structure interactions under rotating conditions.

This work investigates the potential improvements in vehicle fuel economy possible by optimizing gear shift strategies to leverage a novel boosting device, an electrically assisted variable speed supercharger (EAVS), also referred to as a power split supercharger (PSS). Realistic gear shift strategies, resembling those commercially available, have been implemented to control upshift and downshift points based on torque request and engine speed. Using a baseline strategy from a turbocharged application of a MY2015 Ford Escape, a vehicle gas mileage of 34.4 mpg was achieved for the FTP75 drive cycle before considering the best efficiency regions of the supercharged engine.

For better understanding of soot formation and oxidation processes in a biodiesel spray flame, the morphology, microstructure and sizes of soot particles directly sampled in a spray flame fuelled with soy-methyl ester were investigated using transmission electron microscopy (TEM). The soot samples were taken at different axial locations in the spray flame, 40, 50 and 70 mm from injector nozzle, which correspond to soot formation, peak, and oxidation zones, respectively. The biodiesel spray flame was generated in a constant-volume combustion chamber under a diesel-like high pressure and temperature condition (6.7 MPa, 1000K). Density, diameter of primary particles and radius of gyration of soot aggregates reached a peak at 50 mm from the injector nozzle and was lower or smaller in the formation or oxidation zones of the spray.

For a better understanding of soot formation and oxidation processes in conventional diesel and biodiesel spray flames, the morphology, microstructure and sizes of soot particles directly sampled in spray flames fuelled with US#2 diesel and soy-methyl ester were investigated using transmission electron microscopy (TEM). The soot samples were taken at 50mm from the injector nozzle, which corresponds to the peak soot location in the spray flames. The spray flames were generated in a constant-volume combustion chamber under a diesel-like high pressure and high temperature condition (6.7MPa, 1000K). Direct sampling permits a more direct assessment of soot as it is formed and oxidized in the flame, as opposed to exhaust PM measurements. Density of sampled soot particles, diameter of primary particles, size (gyration radius) and compactness (fractal dimension) of soot aggregates were analyzed and compared. No analysis of the soot micro-structure was made.

This paper provides insight into the tradeoffs between exhaust energy recovery and increased pumping losses from the flow restriction of the electric turbo-generator (eTG) assessed using thermodynamic principles and with a detailed GT-Power engine model. The GT-Power engine model with a positive displacement expander model was used to predict the influence of back pressure on in-cylinder residuals and combustion. The eTG is assessed for two boosting arrangements: a conventional turbocharger (TC) and an electrically assisted variable speed (EAVS) supercharger (SC). Both a low pressure (post-turbine) and high pressure (pre-turbine) eTG are considered for the turbocharged configuration. The reduction in fuel consumption (FC) possible over various drive cycles is estimated based on the steady-state efficiency of frequently visited operating points assuming all recovered energy can be reused at an engine efficiency of 30% with 10% losses in the electrical path.

Fundamental engine research is primarily conducted under steady-state conditions, in order to better describe boundary conditions which influence the studied phenomena. However, light-duty automobiles are operated, and tested, under heavily transient conditions. This mismatch between studied conditions and in-use conditions is deemed acceptable due to the fundamental knowledge gained from steady-state experiments. Nonetheless, it is useful to characterize the conditions encountered during transient operation and determine if the governing phenomena are unduly influenced by the differences between steady-state and transient operation, and further, whether transient behavior can be reasonably extrapolated from steady-state behavior. The transient operation mode used in this study consists of 20 fired cycles followed by 80 motored cycles, operating on a continuous basis.

The accurate quantification and control of mixture stoichiometry is critical in many applications using new combustion strategies and fuels (e.g., homogeneous charge compression ignition, gasoline direct injection, and oxygenated fuels). The parameter typically used to quantify mixture stoichiometry (i.e., the proximity of a reactant mixture to its stoichiometric condition) is the equivalence ratio, ϕ. The traditional definition of ϕ is based on the relative amounts of fuel and oxidizer molecules in a mixture. This definition provides an accurate measure of mixture stoichiometry when the fuel molecule does not contain oxidizer elements and when the oxidizer molecule does not contain fuel elements. However, the traditional definition of ϕ leads to problems when the fuel molecule contains an oxidizer element, as is the case when an oxygenated fuel is used, or once reactions have started and the fuel has begun to oxidize.