Search Results

To investigate the feasibility of various test procedures to determine aerodynamic performance for the Phase 2 Greenhouse Gas (GHG) Regulations for Heavy-Duty Vehicles in the United States, the US Environmental Protection Agency commissioned, through Southwest Research Institute, constant-speed torque tests of several heavy-duty tractors matched to a conventional 53-foot dry-van trailer. Torque was measured at the transmission output shaft and, for most tests, also on each of the drive wheels. Air speed was measured onboard the vehicle, and wind conditions were measured using a weather station placed along the road side. Tests were performed on a rural road in Texas. Measuring wind-averaged drag from on-road tests has historically been a challenge. By collecting data in various wind conditions at multiple speeds over multiple days, a regression-based method was developed to estimate wind-averaged drag with a low precision error for multiple tractor-trailer combinations.

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 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.

Portable Emission Measurement Systems (PEMS) are used by the U.S. Environmental Protection Agency (EPA) to measure gaseous and particulate mass emissions from vehicles in normal, in-use, on-the-road operation to support many of its programs, including assessing mobile source emissions compliance, emissions factor assessment for in-use fleet modeling, and collection of in-use vehicle operational data to support vehicle simulation modeling programs. This paper discusses EPA’s use of Global Positioning System (GPS) measured altitude data and electronically logged vehicle speed data to provide real-world road grade data for use as an input into the Gamma Technologies GT-DRIVE+ vehicle model. The GPS measured altitudes and the CAN vehicle speed data were filtered and smoothed to calculate the road grades by using open-source Python code and associated packages.

EPA has been benchmarking engines and transmissions to generate inputs for use in its technology assessments supporting the Midterm Evaluation of EPA’s 2017-2025 Light-Duty Vehicle greenhouse gas emissions assessments. As part of an Atkinson cycle engine technology assessment of applications in light-duty vehicles, cooled external exhaust gas recirculation (cEGR) and cylinder deactivation (CDA) were evaluated. The base engine was a production gasoline 2.0L four-cylinder engine with 75 degrees of intake cam phase authority and a 14:1 geometric compression ratio. An open ECU and cEGR hardware were installed on the engine so that the CO2 reduction effectiveness could be evaluated. Additionally, two cylinders were deactivated to determine what CO2 benefits could be achieved. Once a steady state calibration was complete, two-cycle (FTP and HwFET) CO2 reduction estimates were made using fuel weighted operating modes and a full vehicle model (ALPHA) cycle simulation.

With increasingly stringent light duty particulate emissions regulations, it is of great interest to better understand particulate matter formation. Helping to build the knowledge base for a thorough understanding of particulate matter formation will be an essential step in developing effective control strategies. It is especially important to do this in such a way as to emulate real driving behaviors, including cold starts and transients. To this end, this study examined particulate emissions during transient operation in a recent model year vehicle equipped with a GDI engine. Three of the major federal test cycles were selected as evaluation schemes: the FTP, the HWFET, and the US06. These cycles capture much of the driving behaviors likely to be observed in typical driving scenarios. Measurements included particle size distributions from a TSI EEPS fast-response particle spectrometer, as well as real-time soot emissions from an AVL MSS soot sensor.

The Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool was created by EPA to evaluate the Greenhouse Gas (GHG) emissions of Light-Duty (LD) vehicles [1]. ALPHA is a physics-based, forward-looking, full vehicle computer simulation capable of analyzing various vehicle types combined with different powertrain technologies. The software tool is a MATLAB/Simulink based desktop application. The ALPHA model has been updated from the previous version to include more realistic vehicle behavior and now includes internal auditing of all energy flows in the model [2]. As a result of the model refinements and in preparation for the mid-term evaluation (MTE) of the 2022-2025 LD GHG emissions standards, the model is being revalidated with newly acquired vehicle data. This paper presents an analysis of the effects of varying the absolute and relative gear ratios of a given transmission on carbon emissions and performance.

The Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool was created by EPA to evaluate the Greenhouse Gas (GHG) emissions of Light-Duty (LD) vehicles [1]. ALPHA is a physics-based, forward-looking, full vehicle computer simulation capable of analyzing various vehicle types combined with different powertrain technologies. The software tool is a MATLAB/Simulink based desktop application. The ALPHA model has been updated from the previous version to include more realistic vehicle behavior and now includes internal auditing of all energy flows in the model [2]. As a result of the model refinements and in preparation for the mid-term evaluation (MTE) of the 2022-2025 LD GHG emissions standards, the model is being revalidated with newly acquired vehicle data.

The Advanced Light-Duty Powertrain and Hybrid Analysis tool was created by EPA to evaluate the Greenhouse Gas (GHG) emissions of Light-Duty (LD) vehicles. It is a physics-based, forward-looking, full vehicle computer simulator capable of analyzing various vehicle types combined with different powertrain technologies. The software tool is a freely-distributed, MATLAB/Simulink-based desktop application. Version 1.0 of the ALPHA tool was applicable only to conventional, non-hybrid vehicles and was used to evaluate off-cycle technologies such as air-conditioning, electrical load reduction technology and road load reduction technologies for the 2017-2025 LD GHG rule. The next version of the ALPHA tool will extend its modeling capabilities to include power-split and P2 parallel hybrid electric vehicles and their battery pack energy storage systems. Future versions of ALPHA will incorporate plug-in hybrid electric vehicle (PHEV) and electric vehicle (EV) architectures.

The Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool was created by EPA to evaluate the Greenhouse Gas (GHG) emissions of Light-Duty (LD) vehicles. It is a physics-based, forward-looking, full vehicle computer simulator capable of analyzing various vehicle types combined with different powertrain technologies. The software tool is a freely-distributed, MATLAB/Simulink-based desktop application. Version 1.0 of the ALPHA tool was applicable only to conventional, non-hybrid vehicles and was used to evaluate off-cycle technology such as air-conditioning, electrical load reduction technology and road load reduction technologies for the 2017-2025 LD GHG and Fuel Economy rule. The next version of the ALPHA tool extends its modeling capabilities to include power-split and P2 parallel hybrid electric vehicles and their battery pack energy storage systems. Future versions of ALPHA will incorporate plug-in hybrid electric vehicle (PHEV) and electric vehicle (EV) architectures.

The EPAct/V2/E-89 gasoline fuel effects program collected emissions data for 27 test fuels using a fleet of 15 high-sales cars and light trucks from the 2008 model year (all with port fuel injection). The test fuel matrix covered values of T50, T90, vapor pressure, ethanol content, and total aromatic content spanning ranges typical of market gasolines. Emission measurements were made over the LA92 cycle at a nominal temperature of 24°C (75°F). The resulting emissions database of 956 tests includes a particulate matter (PM) mass measurement for each. Emission models for PM fuel effects were fit based on terms for which the fuel matrix was originally optimized, with results published by EPA in a 2013 analysis report. This paper presents results of a subsequent modeling analysis of this PM data using the PM Index fuel parameter, and compares these models to the original versions.

Because of U.S. EPA regulatory actions and the National Academies National Research Council suggestions for improvements in the U.S. EPA emissions inventory methods, the U.S. EPA' Office of Transportation and Air Quality (OTAQ) has made a concerted effort to develop instrumentation that can measure criteria pollutant emissions during the operation of on-road and off-road vehicles. These instruments are now being used in applications ranging from snowmobiles to on-road passenger cars to trans-Pacific container ships. For the betterment of emissions inventory estimation these on-vehicle instruments have recently been employed to measure time resolved (1 hz) in-use gaseous emissions (CO₂, CO, THC, NO ) and particulate matter mass (with teflon membrane filter) emissions from 29 non-road construction vehicles (model years ranging from 1993 to 2007) over a three year period in various counties in Iowa, Missouri, and Kansas.

A gasoline’s distillation profile is directly related to its hydrocarbon composition and the volatility (boiling points) of those hydrocarbons. Generally, the volatility profiles of U.S. market fuels are characterized using a very simple, low theoretical plate distillation separation, detailed in the ASTM D86 test method. Because of the physical chemistry properties of some compounds in gasoline, this simple still or retort distillation has some limitations: separating azeotropes, isomers, and heavier hydrocarbons. Chemists generally rely on chromatographic separations when more detailed and precise results are needed. High-boiling aromatic compounds are the primary source of particulate emissions from spark ignited (SI), internal combustion engines (ICE), hence a detailed understanding and high-resolution separation of these heavy compounds is needed.

Commercial, class-8 tractor-trailers were tested to develop a relationship between vehicle speed and fuel savings associated with trailer aerodynamic technologies representative of typical long-haul freight applications. This research seeks to address a concern that many long-distance U.S. freight companies hold that, as vehicle speed is reduced, the fuel savings benefits of aerodynamic technologies are not realized. In this paper, the reductions in fuel consumption were measured using the SAE J1231 test method and thru-engine fueling rates recorded from the vehicle’s electronic data stream. Constant speed testing was conducted on road at different speeds and corresponding testing was conducted on track to confirm results. Data was collected at four (4) vehicle speeds: 35, 45, 55, and 62 miles per hour. Two different trailer aerodynamic configurations were evaluated relative to a baseline tractor trailer.

This paper covers work performed for the California Air Resources Board and US Environmental Protection Agency by Southwest Research Institute. Emission measurements were made on four in-use off-road two-stroke motorcycles and all-terrain vehicles utilizing oxygenated and non-oxygenated fuels. Emission data was produced to augment ARB and EPA's off-road emission inventory. It was intended that this program provide ARB and EPA with emission test results they require for atmospheric modeling. The paper describes the equipment and engines tested, test procedures, emissions sampling methodologies, and emissions analytical techniques. Fuels used in the study are described, along with the emissions characterization results. The fuel effects on exhaust emissions and operation due to ethanol content and fuel components is compared.

The Environmental Protection Agency’s (EPA’s) Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool was created to estimate greenhouse gas (GHG) emissions from light-duty vehicles. ALPHA is a physics-based, forward-looking, full vehicle computer simulation capable of analyzing various vehicle types with different powertrain technologies, showing realistic vehicle behavior, and auditing of internal energy flows in the model. In preparation for the midterm evaluation (MTE) of the 2017-2025 light-duty GHG emissions rule, ALPHA has been updated utilizing newly acquired data from model year 2013-2016 engines and vehicles. Simulations conducted with ALPHA provide data on the effectiveness of various GHG reduction technologies, and reveal synergies that exist between technologies. The ALPHA model has been validated against a variety of vehicles with different powertrain configurations and GHG reduction technologies.

The California Air Resources Board (CARB) adopted the Low Emission Vehicle (LEV) III regulations in January 2012, which lowered the particulate matter (PM) emissions standards for light-duty vehicles (LDVs) from 10 milligrams per mile (10 mg/mile) to 3 mg/mile beginning with model year (MY) 2017 and 1 mg/mile beginning with MY 2025. To confirm the ability to measure PM emissions below 1 mg/mile, a total of 23 LDVs (MY pre-2004 to 2009) were tested at CARB's Haagen-Smit Laboratory (HSL) (10 LDVs) and the United States Environmental Protection Agency's (US EPA) National Vehicle and Fuel Emissions Laboratory (NVEFL) (13 LDVs) using the federal test procedure (FTP) drive schedule. One LDV with PM emissions ranging from 0.6 - 0.8 mg/mile was tested at three CARB HSL test cells to investigate intra-lab and inter-lab variability. Reference, trip, and tunnel filter blanks were collected as part of routine quality control (QC) procedures.

Low-pressure loop exhaust gas recirculation (LP- EGR) combined with higher compression ratio, is a technology package that has been a focus of research to increase engine thermal efficiency of downsized, turbocharged gasoline direct injection (GDI) engines. Research shows that the addition of LP-EGR reduces the propensity to knock that is experienced at higher compression ratios [1]. To investigate the interaction and compatibility between increased compression ratio and LP-EGR, a 1.6 L Turbocharged GDI engine was modified to run with LP-EGR at a higher compression ratio (12:1 versus 10.5:1) via a piston change. This paper presents the results of the baseline testing on an engine run with a prototype controller and initially tuned to mimic an original equipment manufacturer (OEM) baseline control strategy running on premium fuel (92.8 anti-knock index).

To investigate the feasibility of various aerodynamic test procedures for the Phase 2 Greenhouse Gas (GHG) Regulations for heavy-duty vehicles in the United States, the US Environmental Protection Agency conducted, through Southwest Research Institute (SwRI), coastdown testing of several heavy-duty tractors matched to a conventional 53-foot dry-van trailer. Three vehicle configurations were tested, two of which included common trailer drag-reduction technologies. Air speed was measured onboard the vehicle, and wind conditions were measured using a weather station placed along the road side. Tests were performed on a rural road in Texas. One vehicle configuration was tested over several days to evaluate day-to-day repeatability and the influence of changing wind conditions. Data on external sources of road forces, such as grade and speed dependence of tire rolling resistance, were collected separately and incorporated into the analysis.