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VTO Annual Progress Report. I. Modeling and Simulation

ParaChoice supports the VTO mission using early-stage research to help in the development of technology that will improve affordability of transportation, while encouraging innovation and reducing dependence on petroleum. Analysis with the ParaChoice model enables exploration of key factors that influence consumer choice, and technology, fuel, and infrastructure development for the vehicle mix. Because of the distinct differences between requirements, needs, and use patterns for light duty vehicles (LDVs) relative to heavy duty vehicles (HDVs), this project models the dynamics of each of these segments to characterize the factors that influence technology adoption.

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History v. Simulation: An Analysis of the Drivers of Alternative Energy Vehicle Sales

Simulations of the US light duty vehicle stock help policy makers, investors, and auto manufacturers make informed decisions to influence the future of the stock and its associated green house gas emissions. Such simulations require an underlying framework that captures the key elements of consumer purchasing decisions, which can be uncertain. This uncertainty in a simulation’s logic is usually convolved with uncertainty in the underlying assumptions about the futures of energy prices and technology innovation and availability. By comparing simulated alternative energy vehicle (AEV) sales to historical sales data, one can assess the simulation’s ability to capture the dynamics of consumer choice, independent of many of those underlying uncertainties, thereby determining the factors that most strongly impact sales. The market for diesel vehicles, hybrid electric vehicles, and to a lesser extent plug-in hybrid electric vehicles and all-electric vehicles, has now matured sufficiently to make such a study possible. In this work, we measure the results of the Sandia ParaChoice model under a variety of input assumptions against historical sales data. Here, we observe that (1) the underlying simulation logic is sound, capturing key drivers of consumer choice, (2) AEV model availability has a significant impact on sales, and (3) AEV consumers are very likely aware of purchasing incentives and factoring those incentives into their purchasing decisions.

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Impact of Workplace and Other Convenient Vehicle Charging

This work uses market analysis and simulation to explore the potential impact of workplace and similarly convenient away-from-home charging infrastructure (AFHCI) in reducing US light duty vehicle (LDV) petroleum use and greenhouse gas emissions. The ParaChoice model simulates the evolution of LDV sales, fuel use, and emissions through 2050, considering consumer responses to different options of electric range extension made available through AFHCI, fraction of the population with access, and delay in infrastructure implementation. Results indicate that providing a greater fraction of the population access to level 1 AFHCI for a full workday may provide more benefit than providing level 2 charging to a lesser fraction. This result holds even considering the fraction of the population without at-home charging. Moreover, delays in infrastructure implementation have no substantial drawbacks for long term petroleum use reduction and EV adoption, though delays will impact short term gains.

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FY2017 Analysis Annual Progress Report

During fiscal year 2017, the U.S. Department of Energy Vehicle Technologies Office (VTO) funded analysis projects supportive of VTO’s goals to pursue early stage research in vehicle and mobility system technologies to reduce petroleum dependence, increase energy reliability and security, improve transportation affordability, and promote economic growth. VTO analysis projects result in a foundation of data, analytical models, and applied analyses that provide insights into critical transportation energy problems and assist in research investment prioritization and portfolio planning.

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FY2018 Analysis Annual Progress Report

During fiscal year 2018 (FY 2018), the U.S. Department of Energy Vehicle Technologies Office (VTO) funded analysis projects supportive of VTO’s goals to pursue early stage research in vehicle and mobility system technologies to improve energy efficiency, increase energy reliability and security, improve transportation affordability, and promote economic growth. VTO analysis projects result in a foundation of data, analytical models, and applied analyses that provide insights into critical transportation energy problems and assist in research investment prioritization and portfolio planning.

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FY2019 Analysis Program Annual Progress Report

The VTO Analysis Program supports mission-critical technology, economic, and interdisciplinary analyses to assist in prioritizing VTO technology investments and to inform research portfolio planning. These efforts provide essential vehicle and market data, modeling and simulation, and integrated and applied analyses, using the unique capabilities, analytical tools, and expertise resident in the national laboratory system.

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Analysis Program Annual Progress Report (FY2020)

During fiscal year 2020 (FY 2020), the U.S. Department of Energy Vehicle Technologies Office (VTO) funded analysis projects supportive of VTO’s goals to pursue early stage research in vehicle and mobility system technologies to reduce petroleum dependence, increase energy reliability and security, improve transportation affordability, and promote economic growth. VTO analysis projects result in a foundation of data, analytical models, and applied analyses that provide insights into critical transportation energy problems and assist in research investment prioritization and portfolio planning. This document presents a brief overview of VTO analysis efforts and progress for projects funded in FY 2020. Each of the progress reports includes project objectives, approach, and highlights of the technical results that were accomplished during the fiscal year.

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Summary of FY17 ParaChoice Accomplishments

As part of analysis support for FCTO, Sandia assesses the factors that influence the future of FCEVs and Hydrogen in the US vehicle fleet. Using ParaChoice, we model competition between FCEVs, conventional vehicles, and other alternative vehicle technologies in order to understand the drivers and sensitivities of adoption of FCEVs. ParaChoice leverages existing tools such as Autonomie (Moawad et al., 2016), AEO (U.S. Energy Information Administration, 2016), and the Macro System Model (Ruth et al., 2009) in order to synthesize a complete picture of the co-evolution of vehicle technology development, energy price evolution, and hydrogen production and pricing, with consumer demand for vehicles and fuel. We then assess impacts of FCEV market penetration and hydrogen use on green- house gas (GHG) emissions and petroleum consumption, providing context for the role of policy, technology development, infrastructure, and consumer behavior on the vehicle and fuel mix through parametric and sensitivity analyses.

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Comparison of Vehicle Choice Models

Five consumer vehicle choice models that give projections of future sales shares of light-duty vehicles were compared by running each model using the same inputs, where possible, for two scenarios. The five models compared — LVCFlex, MA3T, LAVE-Trans, ParaChoice, and ADOPT — have been used in support of the Energy Efficiency and Renewable Energy (EERE) Vehicle Technologies Office in analyses of future light-duty vehicle markets under different assumptions about future vehicle technologies and market conditions. The models give projections of sales shares by powertrain technology. Projections made using common, but not identical, inputs showed qualitative agreement, with the exception of ADOPT. ADOPT estimated somewhat lower advanced vehicle shares, mostly composed of hybrid electric vehicles. Other models projected large shares of multiple advanced vehicle powertrains. Projections of models differed in significant ways, including how different technologies penetrated cars and light trucks. Since the models are constructed differently and take different inputs, not all inputs were identical, but were the same or very similar where possible. Projections by all models were in close agreement only in the first few years. Although the projections from LVCFlex, MA3T, LAVE-Trans, and ParaChoice were in qualitative agreement, there were significant differences in sales shares given by the different models for individual powertrain types, particularly in later years (2030 and later). For example, projected sales shares of conventional spark-ignition vehicles in 2030 for a given scenario ranged from 35% to 74%. Reasons for such differences are discussed, recognizing that these models were not developed to give quantitatively accurate predictions of future sales shares, but to represent vehicles markets realistically and capture the connections between sales and important influences. Model features were also compared at a high level, and suggestions for further comparison of models are given to enable better understanding of how different features and algorithms used in these models may give different projections.

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Comparison of Vehicle Choice Models

Five consumer vehicle choice models that give projections of future sales shares of light-duty vehicles were compared by running each model using the same inputs, where possible, for two scenarios. The five models compared — LVCFlex, MA3T, LAVE-Trans, ParaChoice, and ADOPT — have been used in support of the Energy Efficiency and Renewable Energy (EERE) Vehicle Technologies Office in analyses of future light-duty vehicle markets under different assumptions about future vehicle technologies and market conditions. The models give projections of sales shares by powertrain technology. Projections made using common, but not identical, inputs showed qualitative agreement, with the exception of ADOPT. ADOPT estimated somewhat lower advanced vehicle shares, mostly composed of hybrid electric vehicles. Other models projected large shares of multiple advanced vehicle powertrains. Projections of models differed in significant ways, including how different technologies penetrated cars and light trucks. Since the models are constructed differently and take different inputs, not all inputs were identical, but were the same or very similar where possible.

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