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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.

A prototype 2007 ISL Cummins diesel engine equipped with a diesel oxidation catalyst (DOC), diesel particle filter (DPF), variable geometry turbocharger (VGT), and cooled exhaust gas recirculation (EGR) was tested at Southwest Research Institute (SwRI) under a high-load accelerated durability cycle for 1000 hours with B20 soy-based biodiesel blends and ultra-low sulfur diesel (ULSD) fuel to determine the impact of B20 on engine durability, performance, emissions, and fuel consumption. At the completion of the 1000-hour test, a thorough engine teardown evaluation of the overhead, power transfer, cylinder, cooling, lube, air handling, gaskets, aftertreatment, and fuel system parts was performed. The engine operated successfully with no biodiesel-related failures. Results indicate that engine performance was essentially the same when tested at 125 and 1000 hours of accumulated durability operation.

This paper reports the development of new fuel ignition quality and combustion experiments performed using the Ignition Quality Tester (IQT). Prior SAE papers (961182, 971636, 1999-01-3591, and 2001-01-3527) documented the development of the IQT constant volume combustion chamber experimental apparatus to measure ignition qualities of diesel-type fuels. The ASTM International test method D6890 was developed around the IQT device to allow the rapid determination of derived cetane number (DCN). Interest in chemical kinetic models for the ignition of diesel and biodiesel model compounds is increasing to support the development of advanced engines and fuels. However, rigorous experimental validation of these kinetic models has been limited for a variety of reasons. Shock tubes and rapid compression machines are typically limited to premixed gas-phase studies, for example.

In an effort to characterize the dynamics typical of school bus operation, National Renewable Energy Laboratory (NREL) researchers set out to gather in-use duty cycle data from school bus fleets operating across the country. Employing a combination of Isaac Instruments GPS/CAN data loggers in conjunction with existing onboard telemetric systems resulted in the capture of operating information for more than 200 individual vehicles in three geographically unique domestic locations. In total, over 1,500 individual operational route shifts from Washington, New York, and Colorado were collected. Upon completing the collection of in-use field data using either NREL-installed data acquisition devices or existing onboard telemetry systems, large-scale duty-cycle statistical analyses were performed to examine underlying vehicle dynamics trends within the data and to explore vehicle operation variations between fleet locations.

Battery electric vehicles possess great potential for decreasing lifecycle costs in medium-duty applications, a market segment currently dominated by internal combustion technology. Characterized by frequent repetition of similar routes and daily return to a central depot, medium-duty vocations are well positioned to leverage the low operating costs of battery electric vehicles. Unfortunately, the range limitation of commercially available battery electric vehicles acts as a barrier to widespread adoption. This paper describes the National Renewable Energy Laboratory's collaboration with the U.S. Department of Energy and industry partners to analyze the use of small hydrogen fuel-cell stacks to extend the range of battery electric vehicles as a means of improving utility, and presumably, increasing market adoption.

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.

Annual fuel use for sleeper cab truck rest period idling is estimated at 667 million gallons in the United States, or 6.8% of long-haul truck fuel use. Truck idling during a rest period represents zero freight efficiency and is largely done to supply accessory power for climate conditioning of the cab. The National Renewable Energy Laboratory’s CoolCab project aims to reduce heating, ventilating, and air conditioning (HVAC) loads and resulting fuel use from rest period idling by working closely with industry to design efficient long-haul truck thermal management systems while maintaining occupant comfort. Enhancing the thermal performance of cab/sleepers will enable smaller, lighter, and more cost-effective idle reduction solutions. In addition, if the fuel savings provide a one- to three-year payback period, fleet owners will be economically motivated to incorporate them.

When operated, the cabin climate control system is the largest auxiliary load on a vehicle. This load has significant impact on fuel economy for conventional and hybrid vehicles, and it drastically reduces the driving range of all-electric vehicles (EVs). Heating is even more detrimental to EV range than cooling because no engine waste heat is available. Reducing the thermal loads on the vehicle climate control system will extend driving range and increase the market penetration of EVs. Researchers at the National Renewable Energy Laboratory have evaluated strategies for vehicle climate control load reduction with special attention toward grid-connected electric vehicles. Outdoor vehicle thermal testing and computational modeling were used to assess potential strategies for improved thermal management and to evaluate the effectiveness of thermal load reduction technologies. A human physiology model was also used to evaluate the impact on occupant thermal comfort.

Smart technologies enabling connection among vehicles and between vehicles and infrastructure as well as vehicle automation to assist human operators are receiving significant attention as a means for improving road transportation systems by reducing fuel consumption – and related emissions – while also providing additional benefits through improving overall traffic safety and efficiency. For truck applications, which are currently responsible for nearly three-quarters of the total U.S. freight energy use and greenhouse gas (GHG) emissions, platooning has been identified as an early feature for connected and automated vehicles (CAVs) that could provide significant fuel savings and improved traffic safety and efficiency without radical design or technology changes compared to existing vehicles. A statistical analysis was performed based on a large collection of real-world U.S. truck usage data to estimate the fraction of total miles that are technically suitable for platooning.

In an effort to better understand the operational requirements of port drayage vehicles and their potential for adoption of advanced technologies, National Renewable Energy Laboratory (NREL) researchers collected over 36,000 miles of in-use duty cycle data from 30 Class 8 drayage trucks operating at the Port of Long Beach and Port of Los Angeles in Southern California. These data include 1-Hz global positioning system location and SAE J1939 high-speed controller area network information. Researchers processed the data through NREL’s Drive-Cycle Rapid Investigation, Visualization, and Evaluation tool to examine vehicle kinematic and dynamic patterns across the spectrum of operations. Using the k-medoids clustering method, a repeatable and quantitative process for multi-mode drive cycle segmentation, the analysis led to the creation of multiple drive cycles representing four distinct modes of operation that can be used independently or in combination.

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.

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.

Accurate evaluation of vehicles' transient total power requirement helps achieving further improvements in vehicle fuel efficiency. When operated, the air-conditioning (A/C) system is the largest auxiliary load on a vehicle, therefore accurate evaluation of the load it places on the vehicle's engine and/or energy storage system is especially important. Vehicle simulation models, such as "Autonomie," have been used by OEMs to evaluate vehicles' energy performance. However, the load from the A/C system on the engine or on the energy storage system has not always been modeled in sufficient detail. A transient A/C simulation tool incorporated into vehicle simulation models would also provide a tool for developing more efficient A/C systems through a thorough consideration of the transient A/C system performance. The dynamic system simulation software MATLAB/Simulink® is frequently used by vehicle controls engineers to develop new and more efficient vehicle energy system controls.

Current artificial intelligence techniques for end to end driving of autonomous vehicles typically rely on a single form of learning or training processes along with a corresponding dataset or simulation environment. Relatively speaking, success has been shown for a variety of learning modalities in which it can be shown that the machine can successfully “drive” a vehicle. However, the realm of real-world driving extends significantly beyond the realm of limited test environments for machine training. This creates an enormous gap in capability between these two realms. With their superior neural network structures and learning capabilities, humans can be easily trained within a short period of time to proceed from limited test environments to real world driving.

In some studies, a relationship has been observed between increasing ethanol content in gasoline and increased particulate matter (PM) emissions from vehicles equipped with spark ignition engines. The fundamental cause of the PM increase seen for moderate ethanol concentrations is not well understood. Ethanol features a greater heat of vaporization (HOV) than gasoline and also influences vaporization by altering the liquid and vapor composition throughout the distillation process. A droplet vaporization model was developed to explore ethanol’s effect on the evaporation of aromatic compounds known to be PM precursors. The evolving droplet composition is modeled as a distillation process, with non-ideal interactions between oxygenates and hydrocarbons accounted for using UNIFAC group contribution theory. Predicted composition and distillation curves were validated by experiments.

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.

A new type of solar-reflective glass that improves reflection of the near-infrared (NIR) portion of the solar spectrum has been developed. Also developed was a prototype solar-reflective paint that increases the NIR reflection of opaque vehicle surfaces while maintaining desired colors in the visible portion of the spectrum. Both of these technologies, as well as solar-powered parked car ventilation, were tested on a Cadillac STS as part of the Improved Mobile Air Conditioning Cooperative Research Program (I-MAC). Significant reductions in interior and vehicle skin temperatures were measured. The National Renewable Energy Laboratory (NREL) performed an analysis to determine the impact of reducing the thermal load on the vehicle. A simplified cabin thermal/fluid model was run to predict the potential reduction in A/C system capacity. The potential reduction in fuel use was calculated using a vehicle simulation tool developed by the U.S. Department of Energy (DOE).

Delphi and the National Renewable Energy Laboratory (NREL) collaborated to develop a simulation code to model the mechanical and electrical architectures of a series hybrid vehicle simultaneously. This co-simulation code is part of the larger ADVISOR® product created by NREL and diverse partners. Simulation of the macro power flow in a series hybrid vehicle requires both the mechanical drivetrain and the entire electrical architecture. It is desirable to solve the electrical network equations in an environment designed to comprehend such a network and solve the equations in terms of current and voltage. The electrical architecture for the series hybrid vehicle has been modeled in Saber™ to achieve these goals. This electrical architecture includes not only the high-voltage battery, generator, and traction motor, but also the normal low-voltage bus (14V) with loads common to all vehicles.

Researchers at the National Renewable Energy Laboratory conducted outdoor vehicle thermal soak tests in Golden, Colorado, in September 2002. The same environmental conditions and vehicle were then tested indoors in two DaimlerChrysler test cells, one with metal halide lamps and one with infrared lamps. Results show that the vehicle's shaded interior temperatures correlated well with the outdoor data, while temperatures in the direct sun did not. The large lamp array situated over the vehicle caused the roof to be significantly hotter indoors. Yet, inside the vehicle, the instrument panel was cooler due to the geometry of the lamp array and the spectral difference between the lamps and sun. Results indicate that solar lamps effectively heat the cabin interior in indoor vehicle soak tests for climate control evaluation and SCO3 emissions tests. However, such lamps do not effectively assess vehicle skin temperatures and glazing temperatures.

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.