Novel large scale simulation process to support dot’s cafe modeling system

A. Moawad, P. Balaprakash, A. Rousseau, S. Wild

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

This paper demonstrates a new process that has been specifically designed for the support of the U.S. Department of Transportation’s (DOT’s) Corporate Average Fuel Economy (CAFE) standards. In developing the standards, DOT’s National Highway Traffic Safety Administration made use of the CAFE Compliance and Effects Modeling System (the “Volpe model” or the “CAFE model”), which was developed by DOT’s Volpe National Transportation Systems Center for the 2005–2007 CAFE rulemaking and has been continuously updated since. The model is the primary tool used by the agency to evaluate potential CAFE stringency levels by applying technologies incrementally to each manufacturer’s fleet until the requirements under consideration are met. The Volpe model relies on numerous technology-related and economic inputs, such as market forecasts, technology costs, and effectiveness estimates; these inputs are categorized by vehicle classification, technology synergies, phase-in rates, cost learning curve adjustments, and technology “decision trees”. Part of the model’s function is to estimate CAFE improvements that a given manufacturer could achieve by applying additional technology to specific vehicles in its product line. A significant number of inputs to the Volpe decision-tree model are related to the effectiveness (fuel consumption reduction) of each fuel-saving technology. Argonne National Laboratory has developed a fullvehicle simulation tool named Autonomie, which has become one of the industry’s standard tools for analyzing vehicle energy consumption and technology effectiveness. Full-vehicle simulation tools use physics-based mathematical equations, engineering characteristics (e.g., engine maps, transmission shift points, and hybrid vehicle control strategies), and explicit drive cycles to predict the effectiveness of individual and combined fuel-saving technologies. The Large-Scale Simulation Process accelerates and facilitates the assessment of individual technological impacts on vehicle fuel economy. This paper will show how Argonne efficiently simulates hundreds of thousands of vehicles to model anticipated future vehicle technologies.

Original languageEnglish
Pages (from-to)1067-1077
Number of pages11
JournalInternational Journal of Automotive Technology
Volume17
Issue number6
DOIs
StatePublished - Dec 1 2016
Externally publishedYes

Keywords

  • Autonomie
  • CAFE
  • High performance computing
  • Hybrid vehicles
  • Large scale simulation

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