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Fleet-Level Modeling of Real World Factors Influencing Greenhouse Gas Emission Simulation in ALPHA
- Paul Dekraker - US Environmental Protection Agency ,
- John Kargul - US Environmental Protection Agency ,
- Andrew Moskalik - US Environmental Protection Agency ,
- Kevin Newman - US Environmental Protection Agency ,
- Mark Doorlag - US Environmental Protection Agency ,
- Daniel Barba - US Environmental Protection Agency
ISSN: 1946-3952, e-ISSN: 1946-3960
Published March 28, 2017 by SAE International in United States
Citation: Dekraker, P., Kargul, J., Moskalik, A., Newman, K. et al., "Fleet-Level Modeling of Real World Factors Influencing Greenhouse Gas Emission Simulation in ALPHA," SAE Int. J. Fuels Lubr. 10(1):217-235, 2017, https://doi.org/10.4271/2017-01-0899.
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.
This paper will present an overview of the laboratory benchmarking that was done to support validation of the ALPHA model. The paper discusses a variety of real world factors that influence the simulation of fuel economy and GHG emissions that are often overlooked. Updates have been made to the ALPHA model to reflect additional losses such as tire slip and more detailed representations of the electrical system and accessory loads. The characterization of a core set of future technologies is examined, focusing on developing generic calibrations for driver behavior, transmission gear selection and torque converter lockup that are representative across a wide range of vehicles and transmissions. Finally, the paper illustrates how a set of core future technologies can be used to model GHG emissions from future vehicle fleets.
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