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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.

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 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.

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 (BEVs) offer the potential to reduce both oil imports and greenhouse gas emissions, but high upfront costs, battery-limited vehicle range, and concern over high battery replacement costs may discourage potential buyers. A subscription model in which a service provider owns the battery and supplies access to battery swapping infrastructure could reduce upfront and battery replacement costs with a predictable monthly fee, while expanding BEV range. Assessing the costs and benefits of such a proposal are complicated by many factors, including customer drive patterns, the amount of required infrastructure, battery life, etc. The National Renewable Energy Laboratory has applied its Battery Ownership Model to compare the economics and utility of BEV battery swapping service plan options to more traditional direct ownership options.

Fleet managers need a tool to assist them in assessing their need to comply with EPAct and to provide them with the ability to obtain information that will allow them to make alternative fuel vehicle purchasing decisions. This paper will describe the Web-based tool that will inform a fleet manager, based on their geographic location, the type of fleet they own or operate, and the number and types of vehicles in their fleet, whether or not they need to meet the requirements of EPAct, and, if so, the percentage of new vehicle purchases needed to comply with the law. The tool provides detailed specifications on available OEM alternative fuel vehicles, including the purchase cost of the vehicles, fuel and fuel system characteristics, and incentives and rebates surrounding the purchase of each vehicle. The full set of federal, state, and local incentives is made available through the tool, as well as detailed access to refueling site and dealership locations.

Automobile manufacturers and suppliers are under pressure to develop more efficient thermal management systems as fuel consumption and emission regulations become stricter and buyers demand greater comfort and safety. Additionally, engines must be very efficient and windows must deice and defog quickly. These requirements are often in conflict. Moreover, package styling and cost constraints severely limit the design of coolant and air conditioning systems. Simulation-based design and virtual prototyping can ensure greater product performance and quality at reduced development time and cost. The representation of the vehicle thermal management needs a scalable approach with 0-D, 1-D, and 3-D fluid dynamics, multi-body dynamics, 3-D structural analysis, and control unit simulation capabilities. Different combinations and complexities of the simulation tools are required for various phases of the product development process.

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.

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.

Passenger compartment climate control is one of the largest auxiliary loads on a vehicle. Like conventional vehicles, electric vehicles (EVs) require climate control to maintain occupant comfort and safety, but cabin heating and air conditioning have a negative impact on driving range for all-electric vehicles. Range reduction caused by climate control and other factors is a barrier to widespread adoption of EVs. Reducing the thermal loads on the climate control system will extend driving range, thereby reducing consumer range anxiety and increasing the market penetration of EVs. Researchers at the National Renewable Energy Laboratory have investigated strategies for vehicle climate control load reduction, with special attention toward EVs. Outdoor vehicle thermal testing was conducted on two 2012 Ford Focus Electric vehicles to evaluate thermal management strategies for warm weather, including solar load reduction and cabin pre-ventilation.

Understanding the real-world power demand of modern automobiles is of critical importance to engineers using modeling and simulation in the design of increasingly efficient powertrains. Increased use of global positioning system (GPS) devices has made large-scale data collection of vehicle speed (and associated power demand) a reality. While the availability of real-world GPS data has improved the industry's understanding of in-use vehicle power demand, relatively little attention has been paid to the incremental power requirements imposed by road grade. This analysis quantifies the incremental efficiency impacts of real-world road grade by appending high-fidelity elevation profiles to GPS speed traces and performing a large simulation study. Employing a large, real-world dataset from the National Renewable Energy Laboratory's Transportation Secure Data Center, vehicle powertrain simulations are performed with and without road grade under five vehicle models.

A simple cost analysis framework compares hydrogen and electricity as energy carriers delivering wind energy to light-duty vehicles (LDVs). We compare four wind energy pathways within a 2040-2050 timeframe and at large scale: a dedicated electricity transmission pathway and three distinct wind-hydrogen delivery pathways. Our results suggest that wind-hydrogen pathways will tend to be more costly than pure electricity transmission pathways on a per-mile driven cost basis ($/mile), but to a greater or lesser degree depending upon the pathway. The additional cost could be warranted to the degree that the hydrogen pathway adds value to consumers through full performance fuel cell electric vehicles (FCEV) compared to plug-in electric vehicles (PEVs), or through reduced variability in wind energy supply. If these benefits add value beyond the incremental costs suggested by our simple cost framework, some shift toward co-production or even dedicated hydrogen wind farms may be warranted.

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.

This work presents a methodology to determine the off-cycle fuel economy benefit of a 2-Layer HVAC system which reduces ventilation and heat rejection losses of the heater core versus a vehicle using a standard system. Experimental dynamometer tests using EPA drive cycles over a broad range of ambient temperatures were conducted on a highly instrumented 2016 Lexus RX350 (3.5L, 8 speed automatic). These tests were conducted to measure differences in engine efficiency caused by changes in engine warmup due to the 2-Layer HVAC technology in use versus the technology being disabled (disabled equals fresh air-considered as the standard technology baseline). These experimental datasets were used to develop simplified response surface and lumped capacitance vehicle thermal models predictive of vehicle efficiency as a function of thermal state.

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.

Commercial vehicle fuel economy is known to vary significantly with both positive and negative road grade. Medium- and heavy-duty vehicles operating at highway speeds require incrementally larger amounts of energy to pull heavy payloads up inclines as road grade increases. Non-hybrid vehicles are unable to recapture energy on descent and lose energy through friction braking. While the on-road effects of road grade are well understood, the majority of standard commercial vehicle drive cycles feature no road grade requirements. Additionally, the existing literature offers a limited number of sources that attempt to estimate the on-road energy implications of road grade in the medium- and heavy-duty space. This study uses real-world commercial vehicle drive cycles from the National Renewable Energy Laboratory's Fleet DNA database to simulate the effects of road grade on fuel economy across a range of vocations, operating conditions, and locations.

As the size of spacecraft decreases, the contribution of the power subsystem to the overall spacecraft weight significantly increases. This paper will focus on describing a prototype solar array utilizing three promising technologies to significantly reduce weight, deploy with low shock, and increase packaging efficiency of the solar power system. These technologies are: Copper Indium DiSelenide (CIS) Thin-Film Photovoltaics, Smart Mechanisms Employing Shape Memory, and Multifunctional Structures. Recent advances in shape memory alloy devices, ultralight composites, along with thin-film copper indium diselenide (CIS or CuInSe2) photovoltaics (PV), have shown the potential of providing solar array systems with overall array specific power of >100 W/kg. This results in solar arrays that are a factor of 5 lighter than the current state-of-the-practice, and a factor of 3 lighter than the state-of-the-art.

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.

NREL completed a temporal and geospatial analysis of telematics data to estimate the fraction of platoonable miles traveled by class 8 tractor trailers currently in operation. This paper discusses the value and limitations of very large but low time-resolution data sets, and the fuel consumption reduction opportunities from large scale adoption of platooning technology for class 8 highway vehicles in the US based on telematics data. The telematics data set consist of about 57,000 unique vehicles traveling over 210 million miles combined during a two-week period. 75% of the total fuel consumption result from vehicles operating in top gear, suggesting heavy highway utilization. The data is at a one-hour resolution, resulting in a significant fraction of data be uncategorizable, yet significant value can still be extracted from the remaining data. Multiple analysis methods to estimate platoonable miles are discussed.

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.