Democratization of Electric Vehicle Charging Infrastructure: Analyzing EV Adoption by Vehicle and Household Characteristics Using Synthetic Populations

Trisha Ramadoss, Adam Davis and Gil Tal

Institute of Transportation Studies, Working Paper Series from Institute of Transportation Studies, UC Davis

Abstract: The path to transportation decarbonization will rely heavily on electric vehicles (EVs) in the United States. EV diffusion forecasting tools are necessary to predict the impacts of EVs on local energy demand and environmental quality. Few EV adoption models operate at a fine spatial scale and those that do still rely on aggregated demographic information. This adoption model is one of the first attempts to employ a synthetic population to examine EV distribution at a fine spatial and demographic scale. Using a synthetic population at the Census-Tract-level, enriched with household fleet body types and home-charging access, the researchers consider the effect of vehicle body type on EV spatial distribution and home-charging access in California. The project examines two EV body type mixes in a high electrification scenario where 8 million EVs are distributed across 6 million households in California: a “Small Vehicles” scenario where 6 million EVs are passenger cars and 2 million EVs are trucks, sport utility vehicles (SUVs), or vans and a “Large Vehicles” scenario with 4 million of each category. The authors find that an electrification scenario with more electric trucks and SUVs serves to distribute electrified households more evenly throughout the state, shifting them from urban to rural counties, while there is little impact on home-charging access. View the NCST Project Webpage

Keywords: Physical Sciences and Mathematics; Social and Behavioral Sciences; Automobile ownership; Demographics; Electric vehicle charging; Electric vehicles; Forecasting; Households; Spatial analysis; Vehicle bodies (search for similar items in EconPapers)
Date: 2024-08-31
New Economics Papers: this item is included in nep-ene, nep-env, nep-tre and nep-ure
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