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A program has been completed to evaluate ultra-low sulfur diesel fuels and passive diesel particulate filters (DPFs) in truck and bus fleets operating in southern California. The fuels, ECD and ECD-1, are produced by ARCO (a BP Company) and have less than 15 ppm sulfur content. Vehicles were retrofitted with two types of catalyzed DPFs, and operated on ultra-low sulfur diesel fuel for over one year. Exhaust emissions, fuel economy and operating cost data were collected for the test vehicles, and compared with baseline control vehicles. Regulated emissions are presented from two rounds of tests. The first round emissions tests were conducted shortly after the vehicles were retrofitted with the DPFs. The second round emissions tests were conducted following approximately one year of operation. Several of the vehicles retrofitted with DPFs accumulated well over 100,000 miles of operation between test rounds.

Porous wall permeability is one of the most critical factors for the estimation of backpressure, a key performance indicator in automotive particulate filters. Current experimental and analytical filter models could be calibrated to predict the permeability of a specific filter. However, they fail to provide a reliable estimation for the dependence of the permeability on key parameters such as wall porosity and pore size. This study presents a novel methodology for experimentally determining the permeability of filter walls. The results from four substrates with different porosities and pore sizes are compared with several popular permeability estimation methods (experimental and analytical), and their validity for this application is assessed. It is shown that none of the assessed methods predict all permeability trends for all substrates, for cold or hot flow, indicating that other wall properties besides porosity and pore size are important.

As connected and automated vehicle technologies emerge and proliferate, lower frequency vehicle trajectory data is becoming more widely available. In some cases, entire fleets are streaming position, speed, and telemetry at sample rates of less than 10 seconds. This presents opportunities to apply powertrain simulators such as the National Renewable Energy Laboratory’s Future Automotive Systems Technology Simulator to model how advanced powertrain technologies would perform in the real world. However, connected vehicle data tends to be available at lower temporal frequencies than the 1-10 Hz trajectories that have typically been used for powertrain simulation. Higher frequency data, typically used for simulation, is costly to collect and store and therefore is often limited in density and geography. This paper explores the suitability of lower frequency, high availability, connected vehicle data for detailed powertrain simulation.

The benchmarking study described in this paper uses data from chassis dynamometer testing to determine the efficiency and operation of vehicle driveline components. A robust test procedure was created that can be followed with no a priori knowledge of component performance, nor additional instrumentation installed in the vehicle. To develop the procedure, a 2013 Chevrolet Malibu was tested on a chassis dynamometer. Dynamometer data, emissions data, and data from the vehicle controller area network (CAN) bus were used to construct efficiency maps for the engine and transmission. These maps were compared to maps of the same components produced from standalone component benchmarking, resulting in a good match between results from in-vehicle and standalone testing. The benchmarking methodology was extended to a 2013 Mercedes E350 diesel vehicle. Dynamometer, emissions, and CAN data were used to construct efficiency maps and operation strategies for the engine and transmission.

As part of the U.S. Environmental Protection Agency’s (EPA’s) continuing assessment of advanced light-duty automotive technologies in support of regulatory and compliance programs, the National Vehicle Fuels and Emissions Laboratory has benchmarked multiple transmissions to determine their efficiency during operation. The benchmarking included a modified “coastdown test,” which measures transmission output drag as a function of speed while in neutral. The transmission drag data can be represented as a second-order expression, like that used for vehicle coastdown test results, as F0 + F1V + F2V2, where V is the vehicle velocity. When represented in this fashion, the relationships among the three coefficients were found to be highly predictable. The magnitude of these coefficients can be quite large, and for some tested transmissions the deviation between the quadratic regression and the measured drag at individual velocities can be significant.

As GHG and fuel economy regulations of light-duty vehicles have become more stringent, advanced emissions reduction technology has extensively penetrated the US light-duty vehicle fleet. This new technology includes not only advanced conventional engines and transmissions, but also greater adoption of electrified powertrains. In 2022, electrified vehicles – including mild hybrids, strong hybrids, plug-ins, and battery electric vehicles – made up nearly 17% of the US fleet and are on track to further increase their proportion in subsequent years. The Environmental Protection Agency (EPA) has previously used its Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) full vehicle simulation tool to evaluate the greenhouse gas (GHG) emissions of light-duty vehicles. ALPHA contains a library of benchmarked powertrain components that can be matched to specific vehicles to explore GHG emissions performance.

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.

To make an HCCI engine as a useful commercial product, the engine has to be capable of performing quick transients in a large operating range, especially in vehicle applications. HCCI combustion is kinetically controlled and has to be operated properly between two limits: misfire and knock. To achieve the correct state, the right amount of fuel/air/EGR has to be inducted into the cylinder. The amounts and ratios of the three components are highly dependent on other variables as operating conditions change. It is unrealistic and unreliable to predict the right combination of these variables without principal component analysis. Thus, the optimal response control path has to be based on the quality of the previous combustion event as well as the direction and the rate of transition.

The key hurdles to achieving wide consumer acceptance of battery electric vehicles (BEVs) are weather-dependent drive range, higher cost, and limited battery life. These translate into a strong need to reduce a significant energy drain and resulting drive range loss due to auxiliary electrical loads the predominant of which is the cabin thermal management load. Studies have shown that thermal sub-system loads can reduce the drive range by as much as 45% under ambient temperatures below −10 °C. Often, cabin heating relies purely on positive temperature coefficient (PTC) resistive heating, contributing to a significant range loss. Reducing this range loss may improve consumer acceptance of BEVs. The authors present a unified thermal management system (UTEMPRA) that satisfies diverse thermal and design needs of the auxiliary loads in BEVs.

Due to its high efficiency and superior durability the diesel engine is again becoming a prime candidate for future light-duty vehicle applications within the United States. While in Europe the overall diesel share exceeds 40%, the current diesel share in the U.S. is 1%. Despite the current situation and the very stringent Tier 2 emission standards, efforts are being made to introduce the diesel engine back into the U.S. market. In order to succeed, these vehicles have to comply with emissions standards over a 120,000 miles distance while maintaining their excellent fuel economy. The availability of technologies such as high-pressure common-rail fuel systems, low sulfur diesel fuel, NOx adsorber catalysts (NAC), and diesel particle filters (DPFs) allow the development of powertrain systems that have the potential to comply with the light-duty Tier 2 emission requirements. In support of this, the U.S.

With the advent of stricter vehicle emission standards, the improvement of three way catalyst performance and durability remains a pressing issue. A critical consideration in catalyst design is the potential for variations in fuel sulfur levels to have a significant impact on the ability to reach TLEV, LEV, and ULEV emission levels. As a result, a better understanding of the role of PGM composition in the interplay between thermal durability and sulfur tolerance is required. Three way catalysts representative of standard Pd-only, Pd/Rh and Pt/Rh formulations were studied over a variety of aging and evaluation conditions. The parameters investigated included aging temperature, air fuel ratio and sulfur level. Evaluations were performed on a 1994 TLEV vehicle using different sulfur level fuels. The effect of PGM loading was also included within the study.

In this paper, researchers at the National Renewable Energy Laboratory present the results of simulation studies to evaluate potential fuel savings as a result of improvements to vehicle rolling resistance, coefficient of drag, and vehicle weight as well as hybridization for four powertrains for medium-duty parcel delivery vehicles. The vehicles will be modeled and simulated over 1,290 real-world driving trips to determine the fuel savings potential based on improvements to each technology and to identify best use cases for each platform. The results of impacts of new technologies on fuel saving will be presented, and the most favorable driving routes on which to adopt them will be explored.

Progress made in reducing engine-out particulate emissions has prompted a revival in the design of flow-through oxidation catalysts for diesel engine applications. Effort in this area has focused primarily in the area of SOF control for the further reduction of particulate emissions. The work reported here covers some of the catalyst design parameters important for SOF and gas phase pollutant control. This is illustrated with both laboratory reactor and engine evaluation data for several formulary and operating parameters. Platinum-based catalysts are shown to be generally the most active, but they require treatments or additives to reduce the inherently high activity of platinum for the oxidation of SO2 present in the exhaust. The effect of additives and their loading on the oxidation activity of Pt/alumina for HC, CO, SOF and SO2 oxidation is discussed in detail and additives are identified which reduce SO2 oxidation with minimal effect on HC, CO or SOF oxidation activity.

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.

Exhaust emissions were evaluated for four different catalytic exhaust emission control systems. Each system utilized a diesel oxidation catalyst, a metal-substrate partial-flow diesel particulate filter, an iron-exchanged or copper-exchanged Y-zeolite catalyst for urea selective catalytic reduction, and an ammonia slip catalyst. A 5.9-liter diesel truck engine was modified to match the exhaust conditions of a four-stroke diesel locomotive engine meeting the current Tier 2 locomotive emissions standards. NOx emissions, CO₂ emissions and exhaust temperatures were matched to the eight locomotive "throttle notch" power settings while exhaust mass flow was maintained near a constant fraction of locomotive exhaust mass flow for each "throttle notch" position. Regulated and unregulated exhaust emissions were measured over a steady-state test cycle for each of the four systems at low hours and following accelerated thermal aging and accelerated oil ash accumulation.

As part of its midterm evaluation of the 2022-2025 light-duty greenhouse gas (GHG) standards, the Environmental Protection Agency (EPA) has been acquiring fuel efficiency data from testing of recent engines and vehicles. The benchmarking data are used as inputs to EPA’s Advanced Light Duty Powertrain and Hybrid Analysis (ALPHA) vehicle simulation model created to estimate GHG emissions from light-duty vehicles. For complete powertrain modeling, ALPHA needs both detailed engine fuel consumption maps and transmission efficiency maps. EPA’s National Vehicle and Fuels Emissions Laboratory has previously relied on contractors to provide full characterization of transmission efficiency maps. To add to its benchmarking resources, EPA developed a streamlined more cost-effective in-house method of transmission testing, capable of gathering a dataset sufficient to broadly characterize transmissions within ALPHA.

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.

In previous SAE papers, the initial development and testing of a vacuum-insulated catalytic converter was presented. This paper provides an update of the converter development and an analysis of potential off-cycle emissions savings. Hot vibration, cool-down, and 1975 Federal Test Procedure (FTP-75) emissions test results are provided to demonstrate the effectiveness of design improvements in greatly increasing durability while retaining performance. Using standard drive cycles and “real-world” driving statistics with a vehicle simulator (ADVISOR©), catalyst temperature and vehicle exhaust emissions of a sport utility vehicle (SUV) were predicted for 16 days of driving (107 trips, 770 total miles). Compared to the baseline vehicle with a conventional catalytic converter, the SUV with a vacuum-insulated converter produced 66% less non-methane hydrocarbon (NMHC), 65% less carbon monoxide (CO), and 60% less oxides of nitrogen (NOx).

The emergence of connected and automated vehicles and smart cities technologies create the opportunity for new mobility modes and routing decision tools, among many others. To achieve maximum mobility and minimum energy consumption, it is critical to understand the energy cost of decisions and optimize accordingly. The Route Energy prediction model (RouteE) enables accurate estimation of energy consumption for a variety of vehicle types over trips or sub-trips where detailed drive cycle data are unavailable. Applications include vehicle route selection, energy accounting and optimization in transportation simulation, and corridor energy analyses, among others. The software is a Python package that includes a variety of pre-trained models from the National Renewable Energy Laboratory (NREL). However, RouteE also enables users to train custom models using their own data sets, making it a robust and valuable tool for both fast calculations and rigorous, data-rich research efforts.