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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.

The potential peaking of world conventional oil production and the possible imperative to reduce carbon emissions will put great pressure on vehicle manufacturers to produce more efficient vehicles, on vehicle buyers to seek them out in the marketplace, and on energy suppliers to develop new fuels and delivery systems. Four cases for stabilizing or reducing light vehicle fuel use, oil use, and/or carbon emissions over the next 50 years are presented. Case 1 - Improve mpg so that the fuel use in 2020 is stabilized for the next 30 years. Case 2 - Improve mpg so that by 2030 the fuel use is reduced to the 2000 level and is reduced further in subsequent years. Case 3 - Case 1 plus 50% ethanol use and 50% low-carbon fuel cell vehicles by 2050. Case 4 - Case 2 plus 50% ethanol use and 50% low-carbon fuel cell vehicles by 2050. The mpg targets for new cars and light trucks require that significant advances be made in developing cost-effective and very efficient vehicle technologies.

The National Renewable Energy Laboratory (NREL) collaborated with Millennium Cell and DaimlerChrysler to study heat and water management in a sodium borohydride (NaBH4) storage/processor used to supply hydrogen to a fuel cell in an automotive application. Knowledge of heat and water flows in this system is necessary to maximize the storage concentration of NaBH4, which increases vehicle range. This work helps evaluate the NaBH4 system's potential to meet the FreedomCAR program technical target of 6 wt% hydrogen for hydrogen storage technologies. This paper also illustrates the advantages of integrating the NaBH4 hydrogen processor with the fuel cell.

The impacts of fuel cell system power response capability on optimal hybrid and neat fuel cell vehicle configurations have been explored. Vehicle system optimization was performed with the goal of maximizing fuel economy over a drive cycle. Optimal hybrid vehicle design scenarios were derived for fuel cell systems with 10 to 90% power transient response times of 0, 2, 5, 10, 20, and 40 seconds. Optimal neat fuel cell vehicles where generated for responses times of 0, 2, 5, and 7 seconds. DIRECT, a derivative-free optimization algorithm, was used in conjunction with ADVISOR, a vehicle systems analysis tool, to systematically change both powertrain component sizes and the vehicle energy management strategy parameters to provide optimal vehicle system configurations for the range of response capabilities.

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.

Presently, a main mobility sector objective is to reduce its impact on the global greenhouse gas emissions. While there are many techniques being explored, a promising approach to improve fuel economy is to reduce the required energy by using slipstream effects. This study analyzes the demanded engine power and mechanical energy used by heavy-duty trucks during platooning and non-platooning operation to determine the aerodynamic benefits of the slipstream. A series of platooning tests utilizing class 8 semi-trucks platooning via Cooperative Adaptive Cruise Control (CACC) are performed. Comparing the demanded engine power and mechanical energy used reveals the benefits of platooning on the aerodynamic drag while disregarding any potential negative side effects on the engine. However, energy savings were lower than expected in some cases.

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.

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.

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.

This paper introduces and develops the concept of “Type X” and “Type Y” errors in model validation and calibration, and their implications on extrapolative prediction. Type X error is non-detection of model bias because it is effectively hidden by the uncertainty in the experiments. Possible deleterious effects of Type X error can be avoided by mapping uncertainty into the model until it envelopes the potential model bias, but this likely assigns a larger uncertainty than is needed to account for the actual bias (Type Y error). A philosophy of Best Estimate + Uncertainty modeling and prediction is probably best supported by taking the conservative choice of guarding against Type X error while accepting the downside of incurring Type Y error. An associated methodology involving data- and model- conditioning is presented and tested on a simple but rich test problem.

Laser excitation wavelengths for two-line planar laser-induced fluorescence (PLIF) of 3-pentanone have been optimized for simultaneous imaging of temperature and composition under engine-relevant conditions. Validation of the diagnostic was performed in a motored optical IC engine seeded homogeneously with 3-pentanone. PLIF measurements of the uniform mixture during the compression stroke were used to measure the average temperature and to access the random uncertainty in the measurements. To determine the accuracy of the temperature measurements, experimental average temperatures were compared to values computed assuming isentropic compression and to the output of a tuned 1-D engine simulation. The comparison indicated that the absolute accuracy of the temperature measurements is better than ±5%. Probability density functions (PDFs) calculated from the single-shot images were used to estimate the precision of the measurements.

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.