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Technical Paper

Analyzing the Uncertainty in the Fuel Economy Prediction for the EPA MOVES Binning Methodology

2007-04-16
2007-01-0280
Developed by the U.S. Environmental Protection Agency (EPA), the Multi-scale mOtor Vehicle Emission Simulator (MOVES) is used to estimate inventories and projections through 2050 at the county or national level for energy consumption, nitrous oxide (N2O), and methane (CH4) from highway vehicles. To simulate a large number of vehicles and fleets on numerous driving cycles, EPA developed a binning technique characterizing the energy rate for varying Vehicle Specific Power (VSP) under predefined vehicle speed ranges. The methodology is based upon the assumption that the vehicle behaves the same way for a predefined vehicle speed and power demand. While this has been validated for conventional vehicles, it has not been for advanced vehicle powertrains, including hybrid electric vehicles (HEVs) where the engine can be ON or OFF depending upon the battery State-of-Charge (SOC).
Technical Paper

Comparing Apples to Apples: Well-to-Wheel Analysis of Current ICE and Fuel Cell Vehicle Technologies

2004-03-08
2004-01-1015
Because of their high efficiency and low emissions, fuel-cell vehicles are undergoing extensive research and development. When considering the introduction of advanced vehicles, a complete well-to-wheel evaluation must be performed to determine the potential impact of a technology on carbon dioxide and Green House Gases (GHGs) emissions. Several modeling tools developed by Argonne National Laboratory (ANL) were used to evaluate the impact of advanced powertrain configurations. The Powertrain System Analysis Toolkit (PSAT) transient vehicle simulation software was used with a variety of fuel cell system models derived from the General Computational Toolkit (GCtool) for pump-to-wheel (PTW) analysis, and GREET (Green house gases, Regulated Emissions and Energy use in Transportation) was used for well-to-pump (WTP) analysis. This paper compares advanced propulsion technologies on a well-to-wheel energy basis by using current technology for conventional, hybrid and fuel cell technologies.
Technical Paper

Energy Storage Requirements for Fuel Cell Vehicles

2004-03-08
2004-01-1302
Because of their high efficiency and low emissions, fuel-cell vehicles are undergoing extensive research and development. As the entire powertrain system needs to be optimized, the requirements of each component to achieve FreedomCAR goals need to be determined. With the collaboration of FreedomCAR fuel cell, energy storage, and vehicle Technical Teams, Argonne National Laboratory (ANL) used several modeling tools to define the energy storage requirements for fuel cell vehicles. For example, the Powertrain System Analysis Toolkit (PSAT), which is a transient vehicle simulation software, was used with a transient fuel cell model derived from the General Computational Toolkit (GCtool). This paper describes the impact of degree of hybridization, control strategy, and energy storage technology on energy storage requirements for a fuel cell SUV vehicle platform.
Technical Paper

Feasibility of Reusable Vehicle Modeling:Application to Hybrid Vehicles

2004-03-08
2004-01-1618
Many of today's vehicle modeling tools are good for simulation, but they provide rather limited support for model building and management. Setting up a simulation model requires more than writing down state equations and running them on a computer. The role of a model library is to manage the physics of the system and allow users to share and reuse component models. In this paper, we describe how modern software techniques can be used to support modeling and design activities; the objective is to provide better system models in less time by assembling these system models in a “plug and play” architecture. With the introduction of hybrid electric vehicles, the number of components that can populate a model has increased considerably, and more components translates into more drivetrain configurations. To address these needs, we explain how users can simulate a large number of drivetrain configurations.
Technical Paper

Fuel Economy Sensitivity to Vehicle Mass for Advanced Vehicle Powertrains

2006-04-03
2006-01-0665
In 2002, the U.S. Department of Energy (DOE) launched FreedomCAR, which is a partnership with automakers to advance high-technology research needed to produce practical, affordable advanced vehicles that have the potential to significantly improve fuel economy in the near-term. Advanced materials (including metals, polymers, composites, and intermetallic compounds) can play an important role in improving the efficiency of transportation vehicles. Weight reduction is one of the most practical ways of increasing vehicle fuel economy while reducing exhaust emissions. In this paper, we evaluate the impact of vehicle mass reduction for several vehicle platforms and advanced powertrain technologies, including Internal Combustion Engine (ICE) Hybrid Electric Vehicles (HEVs) and fuel cell HEVs, in comparison with conventional vehicles. We also explain the main factors influencing the fuel economy sensitivity.
Technical Paper

Integrating Data, Performing Quality Assurance, and Validating the Vehicle Model for the 2004 Prius Using PSAT

2006-04-03
2006-01-0667
Argonne National Laboratory (ANL), working with the FreedomCAR Partnership, maintains the hybrid vehicle simulation software, Powertrain System Analysis Toolkit (PSAT). The importance of component models and the complexity involved in setting up optimized control laws require validation of the models and control strategies. Using its Advanced Powertrain Research Facilities (APRF), ANL thoroughly tested the 2004 Toyota Prius to validate the PSAT drivetrain. In this paper, we will first describe the methodology used to quality check test data. Then, we will explain the validation process leading to the simulated vehicle control strategy tuning, which is based on the analysis of the differences between test and simulation. Finally, we will demonstrate the validation of PSAT Prius component models and control strategy, using APRF vehicle test data.
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