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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 program has been completed to evaluate ultra-low sulfur diesel fuels and passive diesel particulate filters (DPFs) in truck and bus fleets operating in southern California. The fuels, ECD and ECD-1, are produced by ARCO (a BP Company) and have less than 15 ppm sulfur content. Vehicles were retrofitted with two types of catalyzed DPFs, and operated on ultra-low sulfur diesel fuel for over one year. Exhaust emissions, fuel economy and operating cost data were collected for the test vehicles, and compared with baseline control vehicles. Regulated emissions are presented from two rounds of tests. The first round emissions tests were conducted shortly after the vehicles were retrofitted with the DPFs. The second round emissions tests were conducted following approximately one year of operation. Several of the vehicles retrofitted with DPFs accumulated well over 100,000 miles of operation between test rounds.

All around the world, steps are being taken to improve the quality of our environment. Prominent among these are the definition, implementation, and attainment of increasingly stringent emissions regulations for all types of engines, including off-highway diesels. These rigorous regulations have driven use of technologies like after-treatment, advanced air systems, and advanced fuel systems. Fuel dispensed off-highway is routinely and significantly dirtier than fuel from on-highway outlets. Furthermore, fuels used in developing countries can be up to 30 times dirtier than the average fuels in North America. Poor fuel cleanliness, coupled with the higher pressures and performance demands of modern fuel systems, create life challenges greater than encountered with cleaner fuels. This can result in costly disruption of operations, loss of productivity, and customer dissatisfaction in the off-highway market.

In recent years, Nearfield Acoustical Holography (NAH) has been used to identify stationary vehicle exterior noise sources. However that application has usually been limited to individual components. Since powertrain noise sources are hidden within the engine compartment, it is difficult to use NAH to identify those sources and the associated partial field that combine to create the complete exterior noise field of a motor vehicle. Integrated Nearfield Acoustical Holography (INAH) has been developed to address these concerns: it is described here. The procedure entails sensing the sources inside the engine compartment by using an array of reference microphones, and then calculating the associated partial radiation fields by using NAH. In the second part of this paper, the use of farfield arrays is considered. Several array techniques have previously been applied to identify noise sources on moving vehicles.

We investigate the mixing, penetration, and ignition characteristics of high-pressure n-dodecane sprays having a split injection schedule (0.5/0.5 dwell/0.5 ms) in a pre-burn combustion vessel at ambient temperatures of 750 K, 800 K and 900 K. High-speed imaging techniques provide a time-resolved measure of vapor penetration and the timing and progression of the first- and second-stage ignition events. Simultaneous single-shot planar laser-induced fluorescence (PLIF) imaging identifies the timing and location where formaldehyde (CH2O) is produced from first-stage ignition and consumed following second-stage ignition. At the 900-K condition, the second injection penetrates into high-temperature combustion products remaining in the near-nozzle region from the first injection. Consequently, the ignition delay for the second injection is shorter than that of the first injection (by a factor of two) and the second injection ignites at a more upstream location near the liquid length.

Shadowgraph/schlieren imaging techniques have often been used for flow visualization of reacting and non-reacting systems. In this paper we show that high-speed shadowgraph visualization in a high-pressure chamber can also be used to identify cool-flame and high-temperature combustion regions of diesel sprays, thereby providing insight into the time sequence of diesel ignition and combustion. When coupled to simultaneous high-speed Mie-scatter imaging, chemiluminescence imaging, pressure measurement, and spatially-integrated jet luminosity measurements by photodiode, the shadowgraph visualization provides further information about spray penetration after vaporization, spatial location of ignition and high-temperature combustion, and inactive combustion regions where problematic unburned hydrocarbons exist. Examples of the joint application of high-speed diagnostics include transient non-reacting and reacting injections, as well as multiple injections.

As connected and automated vehicle technologies emerge and proliferate, lower frequency vehicle trajectory data is becoming more widely available. In some cases, entire fleets are streaming position, speed, and telemetry at sample rates of less than 10 seconds. This presents opportunities to apply powertrain simulators such as the National Renewable Energy Laboratory’s Future Automotive Systems Technology Simulator to model how advanced powertrain technologies would perform in the real world. However, connected vehicle data tends to be available at lower temporal frequencies than the 1-10 Hz trajectories that have typically been used for powertrain simulation. Higher frequency data, typically used for simulation, is costly to collect and store and therefore is often limited in density and geography. This paper explores the suitability of lower frequency, high availability, connected vehicle data for detailed powertrain simulation.

A generalized re-normalization group (RNG) turbulence model based on the local "dimensionality" of the flow field is proposed. In this modeling approach the model coefficients C₁, C₂, and C₃ are all constructed as functions of flow strain rate. In order to further validate the proposed turbulence model, the generalized RNG closure model was applied to model the backward facing step flow (a classic test case for turbulence models). The results indicated that the modeling of C₂ in the generalized RNG closure model is reasonable, and furthermore, the predictions of the generalized RNG model were in better agreement with experimental data than the standard RNG turbulence model. As a second step, the performance of the generalized RNG closure was investigated for a complex engine flow.

Diesel engine combustion is simulated using Large Eddy Simulation (LES) with a multi-mode combustion (MMC) model. The MMC model is based on the combination of chemical kinetics, chemical equilibrium, and quasi-steady flamelet calculations in different local combustion regimes. The local combustion regime is identified by two combustion indices based on the local temperature and the extent of mixture homogeneity. The LES turbulence model uses the dynamic structure model (DSM) for sub-grid stresses. A new spray model in the LES context is used, and the Reynolds-averaged Navier-Stokes (RANS) based wall model is retained with the LES derived scales. These models are incorporated in the KIVA3V-ERC-Release 2 code for engine combustion simulations. A wide range of diesel engine operating conditions were chosen to validate the combustion model.

An Advanced Automotive Manikin (ADAM), is used to evaluate liquid cooling garments (LCG) for advanced space suits for extravehicular applications and launch and entry suits. The manikin is controlled by a finite-element physiological model of the human thermoregulatory system. ADAM's thermal response to a baseline LCG was measured.The local effectiveness of the LCG was determined. These new thermal comfort tools permit detailed, repeatable measurements and evaluation of LCGs. Results can extend to other personal protective clothing including HAZMAT suits, nuclear/biological/ chemical protective suits, fire protection suits, etc.

A full calibration exercise of a diesel engine air path can take months to complete (depending on the number of variables). Model-based calibration approach can speed up the calibration process significantly. This paper discusses the overall calibration process of the air-path of the Cat® C7.1 engine using statistical machine learning tool. The standard Cat® C7.1 engine's twin-stage turbocharger was replaced by a VTG (Variable Turbine Geometry) as part of an evaluation of a novel air system. The changes made to the air-path system required a recalculation of the air path's boost set point and desired EGR set point maps. Statistical learning processes provided a firm basis to model and optimize the air path set point maps and allowed a healthy balance to be struck between the resources required for the exercise and the resulting data quality.

Previous research has shown that the homogeneous charge compression ignition (HCCI) combustion concept holds promise for reducing pollutants (i.e. NOx, soot) while maintaining high thermal efficiency. However, it can be difficult to control the operation of the HCCI engines even under steady state running conditions. Power density may also be limited if high inlet air temperatures are used for achieving ignition. A methodology using a small pilot quantity of diesel fuel injected during the compression stroke to improve the power density and operation control is considered in this paper. Multidimensional computations were carried out for an HCCI engine based on a CAT3401 engine. The computations show that the required initial temperature for ignition is reduced by about 70 K for the cases of the diesel pilot charge and a 25∼35% percent increase in power density was found for those cases without adversely impacting the NOx emissions.

People who wear protective uniforms that inhibit evaporation of sweat can experience reduced productivity and even health risks when their bodies cannot cool themselves. This paper describes a new sweating manikin and a numerical model of the human thermoregulatory system that evaluates the thermal response of an individual to transient, non-uniform thermal environments. The physiological model of the human thermoregulatory system controls a thermal manikin, resulting in surface temperature distributions representative of the human body. For example, surface temperatures of the extremities are cooler than those of the torso and head. The manikin contains batteries, a water reservoir, and wireless communications and controls that enable it to operate as long as 2 hours without external connections. The manikin has 120 separately controlled heating and sweating zones that result in high resolution for surface temperature, heat flux, and sweating control.

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.

One way to increase the load range in an HCCI engine is to increase boost pressure. In this modeling study, we investigate the effect of increased boost pressure on the fuel chemistry in an HCCI engine. Computed results of HCCI combustion are compared to experimental results in a HCCI engine. We examine the influence of boost pressure using a number of different detailed chemical kinetic models - representing both pure compounds (methylcyclohexane, cyclohexane, iso-octane and n-heptane) and multi-component models (primary reference fuel model and gasoline surrogate fuel model). We examine how the model predictions are altered by increased fueling, as well as reaction rate variation, and the inclusion of residuals in our calculations. In this study, we probe the low temperature chemistry (LTC) region and examine the chemistry responsible for the low-temperature heat release (LTHR) for wide ranges of intake boost pressure.

The combined anticipated trends of vehicle sharing (ride-hailing), automated control, and powertrain electrification are poised to disrupt the current paradigm of predominately owner-driven gasoline vehicles with low levels of utilization. Shared, automated, electric vehicle (SAEV) fleets offer the potential for lower cost and emissions and have garnered significant interest among the research community. While promising, unmanaged operation of these fleets may lead to unintended negative consequences. One potentially unintended consequence is a high quantity of SAEVs charging during peak demand hours on the electric grid, potentially increasing the required generation capacity. This research explores the flexibility associated with charging loads demanded by SAEV fleets in response to servicing personal mobility travel demands. Travel demand is synthesized in four major United States metropolitan areas: Detroit, MI; Austin, TX; Washington, DC; and Miami, FL.

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.

Fundamental understanding of the sources of fuel-derived Unburned Hydrocarbon (UHC) emissions in heavy duty diesel engines is a key piece of knowledge that impacts engine combustion system development. Current emissions regulations for hydrocarbons can be difficult to meet in-cylinder and thus after treatment technologies such as oxidation catalysts are typically used, which can be costly. In this work, Computational Fluid Dynamics (CFD) simulations are combined with engine experiments in an effort to build an understanding of hydrocarbon sources. In the experiments, the combustion system design was varied through injector style, injector rate shape, combustion chamber geometry, and calibration, to study the impact on UHC emissions from mixing-controlled diesel combustion.

For better understanding of soot formation and oxidation processes applicable to diesel engines, the size, morphology, and nanostructure of soot particles directly sampled in a diesel spray flame generated in a constant-volume combustion chamber have been investigated using Transmission Electron Microscopy (TEM). For this soot diagnostics, the effects of the sampling processes, TEM observation methodology and image processing methods on the uncertainty in the results have not been extensively discussed, mainly due to the complexity of the analysis.

The goal of this project was to demonstrate a low emissions, high efficiency heavy-duty on-highway natural gas engine. The emissions targets for this project are to demonstrate US 2010 emissions standards on the 13-mode steady state test. To meet this goal, a chemically correct combustion (stoichiometric) natural gas engine with exhaust gas recirculation (EGR) and a three way catalyst (TWC) was developed. In addition, a Sturman Industries, Inc. camless Hydraulic Valve Actuation (HVA) system was used to improve efficiency. A Volvo 11 liter diesel engine was converted to operate as a stoichiometric natural gas engine. Operating a natural gas engine with stoichiometric combustion allows for the effective use of a TWC, which can simultaneously oxidize hydrocarbons and carbon monoxide and reduce NOx. High conversion efficiencies are possible through proper control of air-fuel ratio.