This data supports the project of the same name. The 2019 California Vehicle Survey data was used to analyze the driving behavior associated with more recent EV models (with potentially longer ranges).
This research aims to develop an Artificial Neural Network (ANN) to forecast EVs’ trip destinations and charging behavior–information that is essential for electricity load aggregators to effectively manage charging loads.
This research evaluated the accessibility of federal- and states-level Plug-in Electric Vehicles (PEVs) Income Tax Credits (ITC) policy in the United States, and identified potential barriers for households with diverse income levels, family types and number of children in participation.
The study will utilize mathematical modeling, including artificial intelligence, to design a policy for the
optimal use of plug-in hybrid electric vehicles and identify charging locations for future battery electric vehicle
drivers
This report studies the responses given by PEV lessees and purchasers to the question of what they would do in the absence of the federal tax credit. To analyze the indications made by the responses, researchers sampled 7,000 California PEV drivers and used two logistic regression models and specified them.
This research examines the differentiation between HEV, PHEV and BEV users in Puget Sound Regional Council regarding the aspects of user household socio-demographic attributes, daily travel pattern and energy usage profile.
An increasing diversity of vehicle types, paired with a growing demand for PEVs, has major implications for vehicle miles traveled (VMT), air pollution, and emissions. To better understand what is likely to happen, researchers predict household vehicle preference and VMT by vehicle body and fuel type.
This conference paper discusses interviews conducted with electric vehicle drivers across the U.S. in 2022, which explored their charging experiences at home, work, and public locations, focusing on the use of in-vehicle systems, apps, and information resources, along with pain points, desired features, and opportunities for improving the overall charging experience.
This study differentiates between HEV, PHEV, and BEV users across three factors: owner household socio-demographic attributes, household daily travel patterns, and household energy usage profiles.
To mitigate climate change and air pollution, multiple US states and other countries have been crafting policies aimed at shifting sales from conventional vehicles to plug-in electric vehicles. A key to developing these policies is understanding how financial incentives affect consumers’ decisions to purchase or lease PEVs. To better understand this, researchers at the University of California, Davis, analyzed survey responses from approximately 2,800 California PEV owners.
