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A gas chromatographic technique was used to determine the vapor pressures of blends of six candidate diesel fuel oxygenates with three diesel fuels at 0, 5, 10, 30, and 100 percent blend levels. Both the oxygenates and the diesel fuels were selected to represent a variety of chemical compositions. The vapor pressures were determined over a range of temperatures from -30 C to +30 C. In each case the fraction of the vapor pressure derived from the oxygenate and the fuel was identified. The vapor pressure results showed that there were significant deviations from ideality, leading to both higher and lower vapor pressures than would be predicted from Raoult's Law. These results are significant for fire safety and evaporative emissions as well as for a more basic understanding of the behavior of these blends. Data were also obtained on the heats of vaporization for each of the blends.

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.

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 nodal force based Battelle structural stress method has shown its mesh insensitivity in the stress analysis of spot welds as well as fusion welds. In the conventional structural stress simulation procedure, the structural stress is calculated at the nodes along the nugget periphery. However, implementing a nugget into each spot weld is cumbersome and time consuming not only in preparing mesh for FE analysis but also in preparing a series of structural stress calculation after finishing the FE analysis. Therefore, the efficiency of the current Battelle structural stress practice for spot welds can be improved significantly for structures with a large number of spot welds. The simplified modeling procedure presented here delivers reliable structural stresses at spot welds and these stresses can then be utilized for fatigue life prediction using a master S-N Curve approach that is applicable to wide range of spot welding techniques.

A key to the success of the national hydrogen and fuel cell codes and standards developments efforts to date was the creation and implementation of national templates through which the U.S. Department of Energy (DOE), the National Renewable Energy Laboratory (NREL), and the major standards development organizations (SDOs) and model code organizations coordinate the preparation of critical standards and codes for hydrogen and fuel cell technologies and applications and maintain a coordinated national agenda for hydrogen and fuel cell codes and standards

This paper summarizes the several of the studies in the Environmental Science Program being sponsored by DOE's Office of Heavy Vehicle Technologies (OHVT) through the National Renewable Energy Laboratory (NREL). The goal of the Environmental Science Program is to understand atmospheric impacts and potential health effects that may be caused by the use of petroleum-based fuels and alternative transportation fuels from mobile sources. The Program is regulatory-driven, and focuses on ozone, airborne particles, visibility and regional haze, air toxics, and health effects of air pollutants. Each project in the Program is designed to address policy-relevant objectives. Current projects in the Environmental Science Program have four areas of focus: improving technology for emissions measurements; vehicle emissions measurements; emission inventory development/improvement; ambient impacts, including health effects.

This paper summarizes current work in the Environmental Science & Health Effects (ES&HE) Program being sponsored by DOE's Office of Heavy Vehicle Technologies (OHVT) through the National Renewable Energy Laboratory (NREL). The program is regulatory-driven, and focuses on ozone, airborne particles, visibility and regional haze, air toxics, and health effects of air pollutants. The goal of the ES&HE Program is to understand atmospheric impacts and potential health effects that may be caused by the use of petroleum-based and alternative transportation fuels. Each project in the program is designed to address policy-relevant objectives. Studies in the ES&HE Program have four areas of focus: improving technology for emissions measurements; vehicle emissions measurements, emission inventory development/improvement; and ambient impacts, including health effects.

Hydrogen-powered vehicles offer the promise of significantly reducing the amount of pollutants that are expelled into the environment on a daily basis by conventional hydrocarbon-fueled vehicles. While very promising from an environmental viewpoint, the technology and systems that are needed to store the hydrogen (H2) fuel onboard and deliver it to the propulsion system are different from what consumers, mechanics, fire safety personnel, the public, and even engineers currently know and understand. As the number of hydrogen vehicles increases, the likelihood of a rollover or collision of one of these vehicles with another vehicle or a barrier will also increase.

Reliable assessment of occupant thermal comfort can be difficult to obtain within automotive environments, especially under transient and asymmetric heating and cooling scenarios. Evaluation of HVAC system performance in terms of comfort commonly requires human subject testing, which may involve multiple repetitions, as well as multiple test subjects. Instrumentation (typically comprised of an array of temperature sensors) is usually only sparsely applied across the human body, significantly reducing the spatial resolution of available test data. Further, since comfort is highly subjective in nature, a single test protocol can yield a wide variation in results which can only be overcome by increasing the number of test replications and subjects. In light of these difficulties, various types of manikins are finding use in automotive testing scenarios.

We describe a study to identify potential biofuels that enable advanced spark ignition (SI) engine efficiency strategies to be pursued more aggressively. A list of potential biomass-derived blendstocks was developed. An online database of properties and characteristics of these bioblendstocks was created and populated. Fuel properties were determined by measurement, model prediction, or literature review. Screening criteria were developed to determine if a bioblendstock met the requirements for advanced SI engines. Criteria included melting point (or cloud point) < -10°C and boiling point (or T90) <165°C. Compounds insoluble or poorly soluble in hydrocarbon were eliminated from consideration, as were those known to cause corrosion (carboxylic acids or high acid number mixtures) and those with hazard classification as known or suspected carcinogens or reproductive toxins.

Mixing controlled compression ignition, i.e., diesel engines are efficient and are likely to continue to be the primary means for movement of goods for many years. Low-net-carbon biofuels have the potential to significantly reduce the carbon footprint of diesel combustion and could have advantageous properties for combustion, such as high cetane number and reduced engine-out particle and NOx emissions. We developed a list of over 400 potential biomass-derived diesel blendstocks and populated a database with the properties and characteristics of these materials. Fuel properties were determined by measurement, model prediction, or literature review. Screening criteria were developed to determine if a blendstock met the basic requirements for handling in the diesel distribution system and use as a blend with conventional diesel. Criteria included cetane number ≥40, flashpoint ≥52°C, and boiling point or T90 ≤338°C.

This paper describes a system-level view of a fully automated transit system comprising a fleet of automated vehicles (AVs) in driverless operation, each with an SAE level 4 Automated Driving System, along with its related safety infrastructure and other system equipment. This AV system-level control is compared to the automatic train control system used in automated guideway transit technology, particularly that of communications-based train control (CBTC). Drawing from the safety principles, analysis methods, and risk assessments of CBTC systems, comparable functional subsystem definitions are proposed for AV fleets in driverless operation. With the prospect of multiple AV fleets operating within a single automated mobility district, the criticality of protecting roadway junctions requires an approach like that of automated fixed-guideway transit systems, in which a guideway switch zone “interlocking” at each junction location deconflicts railway traffic, affirming safe passage.

National concerns over energy consumption and emissions from the transportation sector have prompted regulatory agencies to implement aggressive fuel economy targets for light-duty vehicles through the U.S. National Highway Traffic Safety Administration/Environmental Protection Agency (EPA) Corporate Average Fuel Economy (CAFE) program. Automotive manufacturers have responded by bringing competitive technologies to market that maximize efficiency while meeting or exceeding consumer performance and comfort expectations. In a collaborative effort among Toyota Motor Corporation, Argonne National Laboratory (ANL), and the National Renewable Energy Laboratory (NREL), the real-world savings of one such technology is evaluated. A commercially available Toyota Highlander equipped with two-phase cold storage technology was tested at ANL’s chassis dynamometer testing facility.

The National Renewable Energy Laboratory (NREL) has developed a suite of thermal comfort tools to help develop smaller and more efficient climate control systems in automobiles. The tools consist of a thermal comfort manikin, physiological model, and psychological model that are linked together to assess comfort in a transient non-homogeneous environment. The manikin, which consists of 120 individually controlled zones, mimics the human body by heating, sweating, and breathing. The physiological model is a 40,000-node numerical simulation of the human body. The model receives heat loss data from the manikin and predicts the human physiological response and skin temperatures. Based on human subject test data, the psychological model takes the temperatures of the human and predicts thermal sensation and comfort.

An ADvanced Automotive Manikin (ADAM) developed at the National Renewable Energy Laboratory (NREL) is used to evaluate NASA’s liquid cooling garments (LCGs) used in advanced spacesuits. The manikin has 120 separate heated/sweating zones and is controlled by a finite-element physiological model of the human thermo-regulatory system. Previous testing showed the thermal sensation and comfort followed expected trends as the LCG inlet fluid temperature was changed. The Phase II test data demonstrates the repeatability of ADAM by retesting the baseline LCG. Skin and core temperature predictions using ADAM in an LCG/arctic suit combination are compared to NASA physiological data to validate the manikin/model. An additional Orlan LCG configuration is assessed using the manikin and compared to the baseline LCG.

Extensive modeling and simulation studies have been carried out to evaluate the performance of systems for avoiding run-off-road crashes. Results show that the effectiveness of in-vehicle crash avoidance systems depends on how well they can be tailored to specific vehicle, driver, and roadway characteristics. To this end, a major focus of these studies is the development of improved driver lane-keeping models based on statistical analyses of data collected in driving experiments conducted on highways, rural roads, and test tracks. In recent simulation studies using improved driver models, the performance of crash avoidance systems in tractor-trailers and passenger cars has been compared over a wide range of incipient run-off-road crash conditions. Heavy trucks present a greater challenge for run-off-road crash avoidance systems, because they slightly but frequently leave the lane even under controlled driving, and because they are less stable during recovery maneuvers.

Biodiesel has been used to reduce petroleum consumption and pollutant emissions. B20, a 20% blend of biodiesel with 80% petroleum diesel, has become the most common blend used in the United States. Little quantitative information is available on the impact of biodiesel on engine operating costs and durability. In this study, eight engines and fuel systems were removed from trucks that had operated on B20 or diesel, including four 1993 Ford cargo vans and four 1996 Mack tractors (two of each running on B20 and two on diesel). The engines and fuel system components were disassembled, inspected, and evaluated to compare wear characteristics after 4 years of operation and more than 600,000 miles accumulated on B20. The vehicle case history-including mileage accumulation, fuel use, and maintenance costs-was also documented. The results indicate that there was little difference that could be attributed to fuel in operational and maintenance costs between the B20- and diesel-fueled groups.

This paper presents multiple methods for predicting heavy/medium-duty vehicle fuel consumption based on driving cycle information. A polynomial model, a black box artificial neural net model, a polynomial neural network model, and a multivariate adaptive regression splines (MARS) model were developed and verified using data collected from chassis testing performed on a parcel delivery diesel truck operating over the Heavy Heavy-Duty Diesel Truck (HHDDT), City Suburban Heavy Vehicle Cycle (CSHVC), New York Composite Cycle (NYCC), and hydraulic hybrid vehicle (HHV) drive cycles. Each model was trained using one of four drive cycles as a training cycle and the other three as testing cycles. By comparing the training and testing results, a representative training cycle was chosen and used to further tune each method.

Welding induced residual stresses are an important factor to consider when evaluating fatigue design of welded automotive parts. Fortunately, design engineers have various residual stress mitigation technologies at their disposal for improving the fatigue performance of these parts. For this purpose, it is essential to understand the relationship between the residual stresses and fatigue performance quantitatively as well as qualitatively. It has been widely accepted that tensile residual stresses in welded structures are as high as the material yield strength level. Therefore, the fatigue strength of welded joints is governed predominantly by the applied stress range, regardless of the load ratio. However, in stress relieved components the tensile residual stress level is not as high, and the weld fatigue behavior is more influenced by the load ratio.

Efficient and accurate ordinary differential equation (ODE) solvers are necessary for powertrain and vehicle dynamics modeling. However, current commercial ODE solvers can be financially prohibitive, leading to a need for accessible, effective, open-source ODE solvers designed for powertrain modeling. Rust is a compiled programming language that has the potential to be used for fast and easy-to-use powertrain models, given its exceptional computational performance, robust package ecosystem, and short time required for modelers to become proficient. However, of the three commonly used (>3,000 downloads) packages in Rust with ODE solver capabilities, only one has more than four numerical methods implemented, and none are designed specifically for modeling physical systems. Therefore, the goal of the Differential Equation System Solver (DESS) was to implement accurate ODE solvers in Rust designed for the component-based problems often seen in powertrain modeling.