This work uses market analysis and simulation to explore the potential of public charging infrastructure to spur US battery electric vehicle (BEV) sales, increase national electrified mileage, and lower greenhouse gas (GHG) emissions. By employing both scenario and parametric analysis for policy driven injection of public charging stations we find the following: (1) For large deployments of public chargers, DC fast chargers are more effective than level 2 chargers at increasing BEV sales, increasing electrified mileage, and lowering GHG emissions, even if only one DC fast charging station can be built for every ten level 2 charging stations. (2) A national initiative to build DC fast charging infrastructure will see diminishing returns on investment at approximately 30,000 stations. (3) Some infrastructure deployment costs can be defrayed by passing them back to electric vehicle consumers, but once those costs to the consumer reach the equivalent of approximately 12¢/kWh for all miles driven, almost all gains to BEV sales and GHG emissions reductions from infrastructure construction are lost.
Analysis with the ParaChoice model addresses three barriers from the VTO Multi-Year Program Plan: availability of alternative fuels and electric charging station infrastructure, availability of AFVs and electric drive vehicles, and consumer reluctance to purchase new technologies. In this fiscal year, we first examined the relationship between the availability of alternative fuels and station infrastructure. Specifically, we studied how electric vehicle charging infrastructure affects the ability of EVs to compete with vehicles that rely on mature, conventional petroleum-based fuels. Second, we studied how the availability of less costly AFVs promotes their representation in the LDV fleet. Third, we used ParaChoice trade space analyses to help inform which consumers are reluctant to purchase new technologies. Last, we began analysis of impacts of alternative energy technologies on Class 8 trucks to isolate those that may most efficaciously advance HDV efficiency and petroleum use reduction goals.
We present scenario and parametric analyses of the US light duty vehicle (LDV) stock, sim- ulating the evolution of the stock in order to assess the potential role and impacts of fuel cell electric vehicles (FCEVs). The analysis probes the competition of FCEVs with other LDVs and the effects of FCEV adoption on LDV fuel use and emissions. We parameterize commodity and technology prices in order to explore the sensitivities of FCEV sales and emissions to oil, natural gas, battery technology, fuel cell technology, and hydrogen produc- tion prices. We additionally explore the effects of vehicle purchasing incentives for FCEVs, identifying potential impacts and tipping points. Our analyses lead to the following conclu- sions: (1) In the business as usual scenario, FCEVs comprise 7% of all new LDV sales by 2050. (2) FCEV adoption will not substantially impact green house gas emissions without either policy intervention, significant increases in natural gas prices, or technology improve- ments that motivate low carbon hydrogen production. (3) FCEV technology cost reductions have a much greater potential for impact on FCEV sales than hydrogen fuel cost reductions. (4) FCEV purchasing incentives must be both substantial and sustained in order to motivate lasting changes to FCEV adoption.
Our work uses market analysis and simulation to explore the potential of public charging infrastructure to spur US battery electric vehicle (BEV) sales, increase national electrified mileage, and lower greenhouse gas (GHG) emissions. By employing both scenario and parametric analysis for policy driven injection of public charging stations we find the following: (1) For large deployments of public chargers, DC fast chargers are more effective than level 2 chargers at increasing BEV sales, increasing electrified mileage, and lowering GHG emissions, even if only one DC fast charging station can be built for every ten level 2 charging stations. (2) A national initiative to build DC fast charging infrastructure will see diminishing returns on investment at approximately 30,000 stations. (3) Some infrastructure deployment costs can be defrayed by passing them back to electric vehicle consumers, but once those costs to the consumer reach the equivalent of approximately 12¢/kWh for all miles driven, almost all gains to BEV sales and GHG emissions reductions from infrastructure construction are lost.
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.
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.
In the coming decades, light-duty vehicle options and their supporting infrastructure must undergo significant transformations to achieve aggressive national targets for reducing petroleum consumption and lowering greenhouse gas emissions. FCEVs, battery and hybrid electric vehicles, and biofuels are among the promising advanced technology options. This project examines the market penetration of FCEVs in a range of market segments, and in different energy, technology, and policy futures. Analyses are conducted in the context of varying hydrogen production and distribution pathways, as well as public infrastructure availability, fuel (gasoline, ethanol, hydrogen) and electricity costs, vehicle costs and fuel economies to better understand under what conditions, and for which market segments, FCEVs can best compete with battery electric and other alternative fuel vehicles.
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.