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Accurately characterizing vehicle drive cycles plays a fundamental role in assessing the performance of new vehicle technologies. Repeatable, short duration representative drive cycles facilitate more informed decision making, resulting in improved test procedures and more successful vehicle designs. With continued growth in the deployment of onboard telematics systems employing global positioning systems (GPS), large scale, low cost collection of real-world vehicle drive cycle data has become a reality. As a result of these technological advances, researchers, designers, and engineers are no longer constrained by lack of operating data when developing and optimizing technology, but rather by resources available for testing and simulation. Experimental testing is expensive and time consuming, therefore the need exists for a fast and accurate means of generating representative cycles from large volumes of real-world driving data.

Accurate vehicle parameters are valuable for design, modeling, and reporting. Estimating vehicle parameters can be a very time-consuming process requiring tightly-controlled experimentation. This work describes a method to estimate vehicle parameters such as mass, coefficient of drag/frontal area, and rolling resistance using data logged during standard vehicle operation. The method uses a Monte Carlo method to generate parameter sets that are fed to a variant of the road load equation. The modeled road load is then compared to the measured load to evaluate the probability of the parameter set. Acceptance of a proposed parameter set is determined using the probability ratio to the current state, so that the chain history will give a distribution of parameter sets. Compared to a single value, a distribution of possible values provides information on the quality of estimates and the range of possible parameter values. The method is demonstrated by estimating dynamometer parameters.

This paper describes the need for dynamic (transient) simulation of automotive air conditioning systems, the reasons why such simulations are challenging, and the applicability of a general purpose off-the-shelf thermohydraulic analyzer to answer such challenges. An overview of modeling methods for the basic components are presented, along with relevant approximations and their effect on speed and accuracy of the results.

Natural gas, coal, and biomass can be converted to diesel fuel through Fischer-Tropsch (F-T) processes. Variations of the F-T process and/or product work-up can be used to tailor the fuel properties to meet end-users needs. Regardless of feedstock or process, F-T diesel fuels typically have a number of very desirable properties. This review describes typical F-T diesel fuel properties, discusses how these fuel properties impact pollutant emissions, and draws together data from known engine and chassis dynamometer studies of emissions. The comparison of fuel properties reveals that F-T diesel fuel is typically one of two types - a very high cetane number (>74), zero aromatic product or a moderate cetane (∼60), low aromatic (≤15%) product. The very high cetane fuels typically have less desirable low temperature properties while the moderate cetane fuels have cold flow properties more typical of conventional diesel fuels.

How much fuel does vehicle air conditioning actually use? This study attempts to answer that question to determine the national and state-by-state fuel use impact seen by using air conditioning in light duty gasoline vehicles. The study used data from US cities, representative of averages over the past 30 years, whose temperature, incident radiation, and humidity varied through time of day and day of year. National surveys estimated when people drive their vehicles during the day and throughout the year. A simple thermal comfort model based on Fanger's heat balance equations determined the percentage of time that a driver would use the air conditioning based on the premise that if a person were dissatisfied with the thermal environment, they would turn on the air conditioning. Vehicle simulations for typical US cars and trucks determined the fuel economy reduction seen with AC use.

The CRC Fuels for Advanced Combustion Engines working group has worked to identify a matrix of research diesel fuels for use in advanced combustion research applications. Nine fuels were specified and formulated to investigate the effects of cetane number aromatic content and 90% distillation fraction. Standard ASTM analyses were performed on the fuels as well as GC/MS and1H/13C NMR analyses and thermodynamic characterizations. Details of the actual results of the fuel formulations compared with the design values are presented, as well as results from standard analyses, such as heating value, viscosity and density. Cetane number characterizations were accomplished by using both the engine method and the Ignition Quality Tester (IQT™) apparatus.

Evaporative cooling of the fuel-air charge by fuel evaporation is an important feature of direct-injection spark-ignition engines that improves fuel knock resistance and reduces pumping losses at intermediate load, but in some cases, may increase fine particle emissions. We have reported on experimental approaches for measuring both total heat of vaporization and examination of the evaporative heat effect as a function of fraction evaporated for gasolines and ethanol blends. In this paper, we extend this work to include other low-molecular-weight alcohols and present results on species evolution during fuel evaporation by coupling a mass spectrometer to our differential scanning calorimetry/thermogravimetric analysis instrument. The alcohols examined were methanol, ethanol, 1-propanol, isopropanol, 2-butanol, and isobutanol at 10 volume percent, 20 volume percent, and 30 volume percent.

Conventional diesel combustion, also known as Mixing-Controlled Compression Ignition (MCCI), is expected to be the primary power source for medium- and heavy-duty vehicles for decades to come. Displacing petroleum-based ultra-low-sulfur diesel (ULSD) as much as possible with low-net-carbon biofuels will become necessary to help mitigate effects on climate change. Neat biofuels may have difficulty meeting current diesel fuel standards but blends of 30% biofuel in ULSD show potential as ‘drop-in’ fuels. These blends must not make significant changes to the combustion phasing of the MCCI process if they are to be used interchangeably with neat ULSD. An important aspect of MCCI phasing is the ignition delay (ID), i.e. the time between the start of fuel injection and the initial premixed autoignition that initiates the MCCI process.

Transportation vehicle and network system efficiency can be defined in two ways: 1) reduction of travel times across all the vehicles in the system, and 2) reduction in total energy consumed by all the vehicles in the system. The mechanisms to realize these efficiencies are treated as independent (i.e., vehicle and network domains) and, when combined, they have not been adequately studied to date. This research aims to integrate previously developed and published research on Predictive Optimal Energy Management Strategies (POEMS) and Intelligent Traffic Systems (ITS), to address the need for quantifying improvement in system efficiency resulting from simultaneous vehicle and network optimization. POEMS and ITS are partially independent methods which do not require each other to function but whose individual effectiveness may be affected by the presence of the other. In order to evaluate the system level efficiency improvements, the Mobility Energy Productivity (MEP) metric is used.

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.

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.

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.

To help guide heavy vehicle engine, fuel, and exhaust after-treatment technology development, the U.S. Department of Energy and the Lovelace Respiratory Research Institute are conducting research not addressed elsewhere on aspects of the toxicity of particulate engine emissions. Advances in these technologies that reduce diesel particulate mass emissions may result in changes in particle composition, and there is concern that the number of ultrafine (<0.1 micron) particles may increase. All present epidemiological and laboratory data on the toxicity of diesel emissions were derived from emissions of older-technology engines. New, short-term toxicity data are needed to make health-based choices among diesel technologies and to compare the toxicity of diesel emissions to those of other engine technologies.

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.

Spark-ignition engine fuel standards have been put in place to ensure acceptable hot and cold weather driveability (HWD and CWD). Vehicle manufacturers and fuel suppliers have developed systems that meet our driveability requirements so effectively that drivers overwhelmingly find that their vehicles reliably start up and operate smoothly and consistently throughout the year. For HWD, fuels that are too volatile perform more poorly than those that are less volatile. Vapor lock is the apparent cause of poor HWD, but there is conflicting evidence in the literature as to where in the fuel system it occurs. Most studies have found a correlation between degraded driveability and higher dry vapor pressure equivalent or lower TV/L = 20, and less consistently with a minimum T50. For CWD, fuels with inadequate volatility can cause difficulty in starting and rough operation during engine warmup.

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.

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.

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.

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.

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.