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The U.S. Environmental Protection Agency (EPA) contracted with FEV, Inc. to estimate the per-vehicle cost of employing selected advanced efficiency-improving technologies in light-duty motor vehicles. The development of transparent, reliable cost analyses that are accessible to all interested stakeholders has played a crucial role in establishing feasible and cost effective standards to improve fuel economy and reduce greenhouse gas (GHG) emissions. The FEV team, together with engineering staff from EPA's National Vehicle and Fuel Emissions Laboratory, and FEV's subcontractor, Munro & Associates, developed a robust costing methodology based on tearing down, to the piece part level, relevant systems, sub-systems, and assemblies from vehicles ?with and without? the technologies being evaluated.

The objective of this research project was to compare B20 (20% biodiesel fuel) and ultra-low-sulfur (ULSD) diesel-fueled buses in terms of fuel economy, vehicle maintenance, engine performance, component wear, and lube oil performance. We examined 15 model year (MY) 2002 Gillig 40-foot transit buses equipped with MY 2002 Cummins ISM engines. The engines met 2004 U.S. emission standards and employed exhaust gas recirculation (EGR). For 18 months, eight of these buses operated exclusively on B20 and seven operated exclusively on ULSD. The B20 and ULSD study groups operated from different depots of the St. Louis (Missouri) Metro, with bus routes matched for duty cycle parity. The B20- and ULSD-fueled buses exhibited comparable fuel economy, reliability (as measured by miles between road calls), and total maintenance costs. Engine and fuel system maintenance costs were also the same for the two groups after correcting for the higher average mileage of the B20 group.

This research project compares laboratory-measured fuel economy of a medium-duty diesel powered hydraulic hybrid vehicle drivetrain to both a conventional diesel drivetrain and a conventional gasoline drivetrain in a typical commercial parcel delivery application. Vehicles in this study included a model year 2012 Freightliner P10HH hybrid compared to a 2012 conventional gasoline P100 and a 2012 conventional diesel parcel delivery van of similar specifications. Drive cycle analysis of 484 days of hybrid parcel delivery van commercial operation from multiple vehicles was used to select three standard laboratory drive cycles as well as to create a custom representative cycle. These four cycles encompass and bracket the range of real world in-use data observed in Baltimore United Parcel Service operations.

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.

This study compared fuel economy and emissions between heavy-duty hybrid electric vehicles (HEVs) and equivalent conventional diesel vehicles. In-use field data were collected from daily fleet operations carried out at a FedEx facility in California on six HEV and six conventional 2010 Freightliner M2-106 straight box trucks. Field data collection primarily focused on route assessment and vehicle fuel consumption over a six-month period. Chassis dynamometer testing was also carried out on one conventional vehicle and one HEV to determine differences in fuel consumption and emissions. Route data from the field study was analyzed to determine the selection of dynamometer test cycles. From this analysis, the New York Composite (NYComp), Hybrid Truck Users Forum Class 6 (HTUF 6), and California Air Resource Board (CARB) Heavy Heavy-Duty Diesel Truck (HHDDT) drive cycles were chosen.

It is widely understood that cold ambient temperatures increase vehicle fuel consumption due to heat transfer losses, increased friction (increased viscosity lubricants), and enrichment strategies (accelerated catalyst heating). However, relatively little effort has been dedicated to thoroughly quantifying these impacts across a large set of real world drive cycle data and ambient conditions. This work leverages experimental dynamometer vehicle data collected under various drive cycles and ambient conditions to develop a simplified modeling framework for quantifying thermal effects on vehicle energy consumption. These models are applied over a wide array of real-world usage profiles and typical meteorological data to develop estimates of in-use fuel economy. The paper concludes with a discussion of how this integrated testing/modeling approach may be applied to quantify real-world, off-cycle fuel economy benefits of various 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.

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.

As part of the midterm evaluation of the 2022-2025 Light-Duty Vehicle Greenhouse Gas (GHG) Standards, the U.S. Environmental Protection Agency (EPA) developed simulation models for studying the effectiveness of 48V mild hybrid electric vehicle (MHEV) technology for reducing CO2 emissions from light-duty vehicles. Simulation and modeling of this technology requires a suitable model of the battery. This article presents the development and validation of a 48V lithium-ion battery model that will be integrated into EPA’s Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) vehicle simulation model and that can also be used within Gamma Technologies, LLC (Westmont, IL) GT-DRIVE™ vehicle simulations. The battery model is a standard equivalent circuit model with the two-time constant resistance-capacitance (RC) blocks.

Modeling and simulation are crucial in the development of advanced energy efficient control strategies. Utilizing real-world driving data as the underlying basis for control design and simulation lends veracity to projected real-world energy savings. Standardized drive cycles are limited in their utility for evaluating advanced driving strategies that utilize connectivity and on-vehicle sensing, primarily because they are typically intended for evaluating emissions and fuel economy under controlled conditions. Real-world driving data, because of its scale, is a useful representation of various road types, driving styles, and driving environments. The scale of real-world data also presents challenges in effectively using it in simulations. A fast and efficient simulation methodology is necessary to handle the large number of simulations performed for design analysis and impact evaluation of control strategies.

Due to raising interest in diesel powered passenger cars in the U.S. in combination with a desire to reduce dependency on imported petroleum, there has been increased attention to the operation of diesel vehicles on fuels blended with biodiesel. One of several factors to be considered when operating a vehicle on biodiesel blends is understanding the impact and performance of the fuel on the emission control system. This paper documents the impact of the biodiesel blends on engine-out emissions as well as the overall system performance in terms of emission control system calibration and the overall system efficiency. The testing platform is a light-duty HSDI diesel engine with a Euro 4 base calibration in a 1700 kg sedan vehicle. It employs 2nd generation common-rail injection system with peak pressure of 1600 bar as well as cooled high-pressure EGR. The study includes 3 different fuels (U.S.

Raising interest in Diesel powered passenger cars in the United States in combination with the government mandated policy to reduce dependency of foreign oil, leads to the desire of operating Diesel vehicles with Biodiesel fuel blends. There is only limited information related to the impact of Biodiesel fuels on the performance of advanced emission control systems. In this project the implementation of a NOx storage and a SCR emission control system and the development for optimal performance are evaluated. The main focus remains on the discussion of the differences between the fuels which is done for the development as well as useful life aged components. From emission control standpoint only marginal effects could be observed as a result of the Biodiesel operation. The NOx storage catalyst results showed lower tailpipe emissions which were attributed to the lower exhaust temperature profile during the test cycle. The SCR catalyst tailpipe results were fuel neutral.

Experiments were conducted with ultra low sulfur diesel (ULSD) and 20% biodiesel blends (B20) to compare lube oil dilution levels and lubricant properties for systems using late in-cylinder fuel injection for aftertreatment regeneration. Lube oil dilution was measured by gas chromatography (GC) following ASTM method D3524 to measure diesel content, by Fourier transform infrared (FTIR) spectrometry following a modified ASTM method D7371 to measure biodiesel content, and by a newly developed back-flush GC method that simultaneously measures both diesel and biodiesel. Heavy-duty (HD) engine testing was conducted on a 2008 6.7L Cummins ISB equipped with a diesel oxidation catalyst (DOC) and diesel particle filter (DPF). Stage one of engine testing consisted of 10 consecutive repeats of a forced DPF regeneration event. This continuous operation with late in-cylinder fuel injection served as a method to accelerate lube-oil dilution.

While it is well known that “MPG will vary” based on how one drives, little independent research exists on the aggregate fuel savings potential of improving driver efficiency and on the best ways to motivate driver behavior changes. This paper finds that reasonable driving style changes could deliver significant national petroleum savings, but that current feedback approaches may be insufficient to convince many people to adopt efficient driving habits. To quantify the outer bound fuel savings for drive cycle modification, the project examines completely eliminating stop-and-go driving plus unnecessary idling, and adjusting acceleration rates and cruising speeds to ideal levels. Even without changing the vehicle powertrain, such extreme adjustments result in dramatic fuel savings of over 30%, but would in reality only be achievable through automated control of vehicles and traffic flow.

The U.S. Environmental Protection Agency (EPA) contracted with FEV, Inc. to estimate the per-vehicle cost of employing selected advanced efficiency-improving technologies in light-duty motor vehicles. The development of transparent, reliable cost analyses that are accessible to all interested stakeholders has played a crucial role in establishing feasible and cost effective standards to improve fuel economy and reduce greenhouse gas (GHG) emissions. The FEV team, together with engineering staff from EPA's National Vehicle and Fuel Emissions Laboratory, and FEV's subcontractor, Munro & Associates, developed a robust costing methodology based on tearing down, to the piece part level, relevant systems, sub-systems, and assemblies from vehicles “with and without” the technologies being evaluated.

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.

Current SAE practices for evaluating potential improvements in fuel economy on heavy-duty vehicles rely on gravimetric measurements of fuel tanks. However, the recent evolution of portable emissions measurement systems (PEMS) offers an alternative means of evaluating real-world fuel economy that may be faster and more cost effective. This paper provides a direct comparison of these two methods based on a recent EPA study conducted at Southwest Research Institute. More than 228 on-road tests were performed on two pairs of class 8 tractor-trailers according to SAE test procedure J1321 in an assessment of various chassis components designed to reduce drag losses on the vehicle. During these tests, SEMTECH-D™ portable emissions measurement systems from Sensor's, Incorporated were operating in each of the vehicles to evaluate emissions and to provide a redundant measure of fuel economy.

As part of the U.S. Environmental Protection Agency’s (EPA’s) continuing assessment of advanced light-duty (LD) automotive technologies to support the setting of appropriate national greenhouse gas (GHG) standards and to evaluate the impact of new technologies on in-use emissions, a 2016 Honda Civic with a 4-cylinder 1.5-liter L15B7 turbocharged engine and continuously variable transmission (CVT) was benchmarked. The test method involved installing the engine and its CVT in an engine-dynamometer test cell with the engine wiring harness tethered to its vehicle parked outside the test cell. Engine and transmission torque, fuel flow, key engine temperatures and pressures, and onboard diagnostics (OBD)/Controller Area Network (CAN) bus data were recorded.

The objective of this research project was to compare the emissions of oxides of nitrogen (NOx) from transit buses on as many as five different fuels and three standard transit duty cycles to establish if there is a real-world biodiesel NOx increase for transit bus duty cycles and engine calibrations. Prior studies have shown that B20 can cause a small but significant increase in NOx emissions for some engines and duty cycles. Six buses spanning engine build years 1998 to 2011 were tested on the National Renewable Energy Laboratory's Renewable Fuels and Lubricants research laboratory's heavy-duty chassis dynamometer with certification diesel, certification B20 blend, low aromatic [California Air Resources Board (CARB)] diesel, low aromatic B20 blend, and B100 fuels over the Manhattan, Orange County and UDDS test cycles.