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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.

Chassis dynamometer tests were conducted on three Class III on-highway motorcycles produced for the North American market and equipped with advanced emission control technologies in order to inform emissions inventories and compare the impacts of existing Tier 2 (E0) fuel with more market representative Tier 3 and LEV III certification fuels with 10% ethanol. For this study, the motorcycles were tested over the US Federal Test Procedure (FTP) and the World Motorcycle Test Cycle (WMTC) certification test cycles as well as a sample of real-world motorcycle driving informally referred to as the Real World Driving Cycle (RWDC). The primary interest was to understand the emissions changes of the selected motorcycles with the use of certification fuels containing 10% ethanol compared to 0% ethanol over the three test cycles.

In light-duty vehicles, there is a fundamental trade-off between fuel consumption and acceleration performance, if other vehicle attributes are held fixed. Earlier econometric studies have estimated the magnitude of this trade-off - the elasticity of fuel consumption with respect to performance - based on historical vehicle data. The majority of these studies assume, a priori, that elasticity is constant across the model year, vehicle power, and technology content. However, there is evidence that the content in the underlying powertrain technology packages is shifting in a way that reduces the value of the elasticity of fuel consumption with respect to performance, such that historical trends would not predict future behavior. This paper presents an alternative strategy for studying vehicle fuel consumption versus performance trade-off.

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, a 2018 Toyota Camry front wheel drive eight-speed automatic transmission was benchmarked. The benchmarking data were used as inputs to EPA’s Advanced Light-duty Powertrain and Hybrid Analysis (ALPHA) vehicle simulation model to estimate GHG emissions from light-duty vehicles. ALPHA requires both detailed engine fuel consumption maps and transmission torque loss maps. EPA’s National Vehicle and Fuels Emissions Laboratory has developed a streamlined, cost-effective in-house method of transmission testing, capable of gathering a dataset sufficient to characterize transmissions within ALPHA. This testing methodology targets the range of transmission operation observed during vehicle testing over EPA’s city and highway drive cycles.

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.

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.

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.

By almost any definition, technology has penetrated the U.S. light-duty vehicle fleet significantly in conjunction with the increased stringency of fuel economy and GHG emissions regulations. The physical presence of advanced technology components provides one indication of the efforts taken to reduce emissions, but that alone does not provide a complete measure of the benefits of a particular technology application. Differences in the design of components, the materials used, the presence of other technologies, and the calibration of controls can impact the performance of technologies in any particular implementation. The effectiveness of a technology for reducing emissions will also be influenced by the extent to which the technologies are applied towards changes in vehicle operating characteristics such as improved acceleration, or customer features that may offset mass reduction from the use of lightweight materials.

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).

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.

The U.S. 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 all energy flows in the model. In preparation for the midterm evaluation (MTE) of the 2017-2025 light-duty GHG emissions rule, ALPHA has been refined and revalidated using newly acquired data from model year 2013-2016 engines and vehicles. The robustness of EPA’s vehicle and engine testing for the MTE coupled with further validation of the ALPHA model has highlighted some areas where additional data can be used to add fidelity to the engine model within ALPHA.

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 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.

As part of its technology assessment for the upcoming midterm evaluation (MTE) of the 2022-2025 Light-Duty Vehicle Greenhouse Gas (LD GHG) emissions standards, EPA has been benchmarking engines and transmissions to generate inputs for use in its Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) model, a physics-based, forward-looking, full vehicle computer simulation tool. One of the most efficient engines today, a 2.0L Mazda SkyActiv engine, is of particular interest due to its high geometric compression ratio and use of an Atkinson cycle. EPA benchmarked the 2.0L SkyActiv at its National Vehicle and Fuel Emissions laboratory. EPA then incorporated ALPHA into an engine dynamometer control system so that vehicle chassis testing could be simulated with a hardware-in-the-loop (HIL) approach.

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 (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.

In preparation for the midterm evaluation (MTE) of the 2022-2025 Light-Duty Greenhouse Gas (LD GHG) emissions standards, the Environmental Protection Agency (EPA) is refining and revalidating their Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool using newly acquired data from model year 2013-2015 engines and 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 all internal energy flows in the model. As part of the validation of ALPHA, the EPA obtained model year 2014 Dodge Chargers equipped with 3.6 liter V6 engines and either a NAG1 five-speed automatic transmission or an 845RE eight-speed automatic transmission.

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.

The Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool was created by EPA to estimate greenhouse gas (GHG) emissions from 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. In order to model the behavior of current and future vehicles, an algorithm was developed to dynamically generate transmission shift logic from a set of user-defined parameters, a cost function (e.g., engine fuel consumption) and vehicle performance during simulation. This paper presents ALPHA's shift logic algorithm and compares its predicted shift points to actual shift points from a mid-size light-duty vehicle and to the shift points predicted using a static table-based shift logic as calibrated to the same vehicle during benchmark testing.

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.