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Journal Article

Characterizing Factors Influencing SI Engine Transient Fuel Consumption for Vehicle Simulation in ALPHA

2017-03-28
2017-01-0533
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.
Journal Article

Benchmarking a 2016 Honda Civic 1.5-Liter L15B7 Turbocharged Engine and Evaluating the Future Efficiency Potential of Turbocharged Engines

2018-04-03
2018-01-0319
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.
Technical Paper

Benchmarking and Hardware-in-the-Loop Operation of a 2014 MAZDA SkyActiv 2.0L 13:1 Compression Ratio Engine

2016-04-05
2016-01-1007
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.
Technical Paper

Estimating GHG Reduction from Combinations of Current Best-Available and Future Powertrain and Vehicle Technologies for a Midsized Car Using EPA’s ALPHA Model

2016-04-05
2016-01-0910
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[1]. 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. The software tool is a MATLAB/Simulink based desktop application. In preparation for the midterm evaluation of the light-duty GHG emission standards for model years 2022-2025, EPA is refining and revalidating ALPHA using newly acquired data from model year 2013-2015 engines and vehicles.
Technical Paper

Constructing Engine Maps for Full Vehicle Simulation Modeling

2018-04-03
2018-01-1412
The Environmental Protection Agency (EPA) has collected a variety of engine and vehicle test data to assess the effectiveness of new automotive technologies in meeting greenhouse gas (GHG) and criteria emission standards and to monitor their behavior in real world operation. EPA’s Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool was created to estimate GHG emissions from vehicles using various combinations of advanced technologies and has been refined using data from testing conducted at EPA’s National Vehicle and Fuel Emissions Laboratory. This paper describes a process for constructing complete engine maps using engine dynamometer and in-vehicle test data for use in ALPHA or any other full vehicle simulation which performs similar analyses. The paper reviews how to use available steady state and transient test data to characterize different operating conditions, and then combine the data to construct a complete engine map suitable for ALPHA model simulation.
Technical Paper

Modeling the Effects of Transmission Gear Count, Ratio Progression, and Final Drive Ratio on Fuel Economy and Performance Using ALPHA

2016-04-05
2016-01-1143
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.
Journal Article

Fleet-Level Modeling of Real World Factors Influencing Greenhouse Gas Emission Simulation in ALPHA

2017-03-28
2017-01-0899
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.
Journal Article

Development of Greenhouse Gas Emissions Model (GEM) for Heavy- and Medium-Duty Vehicle Compliance

2015-09-29
2015-01-2771
In designing a regulatory vehicle simulation program for determining greenhouse gas (GHG) emissions and fuel consumption, it is necessary to estimate the performance of technologies, verify compliance with the regulatory standards, and estimate the overall benefits of the program. The agencies (EPA/NHTSA) developed the Greenhouse Gas Emissions Model (GEM) to serve these purposes. GEM is currently being used to certify the fuel consumption and CO2 emissions of the Phase 1 rulemaking for all heavy-duty vehicles in the United States except pickups and vans, which require a chassis dynamometer test for certification. While the version of the GEM used in Phase 1 contains most of the technical and mathematical features needed to run a vehicle simulation, the model lacks sophistication. For example, Phase 1 GEM only models manual transmissions and it does not include engine torque interruption during gear shifting.
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