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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.

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.

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.

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).

With ongoing concerns about the elevated levels of ambient air pollution in urban areas and the contribution from heavy-duty diesel vehicles, hybrid electric vehicles are considered as a potential solution as they are perceived to be more fuel efficient and less polluting than their conventional engine counterparts. However, recent studies have shown that real-world emissions may be substantially higher than those measured in the laboratory, mainly due to operating conditions that are not fully accounted for in dynamometer test cycles. At the U.S. EPA National Fuel and Vehicle Emissions Laboratory (NVFEL) the in-use criteria emissions and energy efficiency of heavy-duty class 8 vehicles (up to 36280 kg) can be evaluated under controlled conditions in the heavy-duty chassis dynamometer test.

Energy security and climate change challenges provide a strong impetus for investigating Electric Vehicle (EV) concepts. EVs link two major infrastructures, the transportation and the electric power grid. This provides a chance to bring other sources of energy into transportation, displace petroleum and, with the right mix of power generation sources, reduce CO₂ emissions. The main obstacles for introducing a large numbers of EVs are cost, battery weight, and vehicle range. Battery health is also a factor, both directly and indirectly, by introducing limits on depth of discharge. This paper considers a low-cost path for extending the range of a small urban EV by integrating a parallel hydraulic system for harvesting and reusing braking energy. The idea behind the concept is to avoid replacement of lead-acid or small Li-Ion batteries with a very expensive Li-Ion pack, and instead use a low-cost hydraulic system to achieve comparable range improvements.

Light-duty vehicle greenhouse gas (GHG) and fuel economy (FE) standards for MYs 2012-2025 are requiring vehicle powertrains to become much more efficient. One key technology strategy that vehicle manufacturers are using to help comply with GHG and FE standards is to replace naturally aspirated engines with smaller displacement “downsized” boosted engines. In order to understand and measure the effects of this technology, the Environmental Protection Agency (EPA) benchmarked a 2013 Ford Escape with an EcoBoost® 1.6L engine. This paper describes a “tethered” engine dyno benchmarking method used to develop a fuel efficiency map for the 1.6L EcoBoost® engine. The engine was mounted in a dyno test cell and tethered with a lengthened engine wire harness to a complete 2013 Ford Escape vehicle outside the test cell. This method allowed engine mapping with the stock ECU and calibrations.

The Advanced Light-Duty Powertrain and Hybrid Analysis tool was created by Environmental Protection Agency to evaluate the greenhouse gas emissions and fuel efficiency of light-duty vehicles. It is a physics-based, forward-looking, full vehicle computer simulator that is capable of analyzing various vehicle types equipped with different powertrain technologies. The software is built on MATLAB/Simulink. This first version release of the simulation tool models conventional vehicles and is capable of evaluating effects of off-cycle technologies on greenhouse gas emissions, such as air conditioning, electrical load reduction, road load reduction by active aerodynamics, and engine start-stop. This paper introduces the simulation tool by describing its basic model architecture and presenting its underlying physics as well as model formulations. It describes the simulation capability along with its graphical user interface of the tool, designed for off-cycle technology analysis purposes.

During the 1980s, the U.S. Environmental Protection Agency (EPA) incorporated the R factor into fuel economy calculations in order to address concerns about the impacts of test fuel property variations on corporate average fuel economy (CAFE) compliance, which is determined using the Federal Test Procedure (FTP) and Highway Fuel Economy Test (HFET) cycles. The R factor is defined as the ratio of the percent change in fuel economy to the percent change in volumetric heating value for tests conducted using two differing fuels. At the time the R-factor was devised, tests using representative vehicles initially indicated that an appropriate value for the R factor was 0.6. Reassessing the R factor has recently come under renewed interest after EPA's March 2013 proposal to adjust the properties of certification gasoline to contain significant amounts of ethanol.

In June of 2015, the Environmental Protection Agency and the National Highway Traffic Safety Administration issued a Notice of Proposed Rulemaking to further reduce greenhouse gas emissions and improve the fuel efficiency of medium- and heavy-duty vehicles. The agencies proposed that vehicle manufacturers would certify vehicles to the standards by using the agencies’ Greenhouse Gas Emission Model (GEM). The agencies also proposed a steady-state engine test procedure for generating GEM inputs to represent the vehicle’s engine performance. In the proposal the agencies also requested comment on an alternative engine test procedure, the details of which were published in two separate 2015 SAE Technical Papers [1, 2]. As an alternative to the proposed steady-state engine test procedure, these papers presented a cycle-average test procedure.

In response to more stringent greenhouse gas and fuel economy standards and increasing consumer demand for fuel efficient vehicles, automobile manufacturers have identified vehicle mass reduction as a leading strategy for reducing greenhouse gas emissions and improving fuel economy. The potential for significant levels of mass reduction can only be understood using a full-vehicle analysis, partly because mass reduction in one vehicle system or part can enable additional reductions elsewhere. This paper describes a holistic approach in which the most cost-effective mass reduction ideas were selected using a structured optimization procedure, and the crash safety of the resultant design was evaluated using a full-vehicle engineering analysis.

The U.S. Environmental Protection Agency, U.S. Department of Transportation's National Highway and Traffic Safety Administration, and the California Air Resources Board have recently released proposed new regulations for greenhouse gas emissions and fuel economy for light-duty vehicles and trucks in model years 2017-2025. These proposed regulations intend to significantly reduce greenhouse gas emissions and increase fleet fuel economy from current levels. At the fleet level, these rules the proposed regulations represent a 50% reduction in greenhouse gas emissions by new vehicles in 2025 compared to current fleet levels. At the same time, global growth, especially in developing economies, should continue to drive demand for crude oil and may lead to further fuel price increases. Both of these trends will therefore require light duty vehicles (LDV) to significantly improve their greenhouse gas emissions over the next 5-15 years to meet regulatory requirements and customer demand.