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 study aims to investigate the influence of regenerative brake system on the brake PM emissions using vehicles which has both battery electric vehicle, electric vehicle, and internal combustion engine (ICE) versions, or hydrogen electric vehicles and ICE versions.
Researchers at the University of California, Riverside aimed to establish a test method to determine brake activity of a heavy-duty vehicle under both dynamometer tests and on-road tests.
This report presents a survey of the latest advancements in battery technologies, primarily focusing on Class 7 and Class 8 heavy-duty vehicles due to their critical role in freight transport.
To meet sales requirements of zero-emission transit buses, medium-duty (MD) trucks, and heavy-duty (HD) trucks in California, improvements in battery performance and costs are necessary. This project will support this transition through analysis of battery capabilities, charging infrastructure availability, and vehicle routing strategies.
The report explores the necessity to correctly estimate the preference for vehicle holdings of households as well as the vehicle miles traveled by vehicle body- and fuel-type to project future Vehicle Miles Traveled changes and mobile source emission levels. The report presents the application of a utility-based model for multiple discreteness that combines multiple vehicle types with usage in an integrated model, specifically the MDCEV model.
Principal InvestigatorDebapriya Chakraborty, Ph.D.
University of California, Davis
This project will involve a robust analysis of plug-in electric vehicle choice and usage decisions by households within an integrated framework that captures the joint nature of the decisions.
In this study, the researchers will use optimization and simulation modeling to explore the impacts of using battery electric heavy-duty trucks (BEHDTs) in freight operations (e.g., fleet size) and emissions, taking into account differences in performance and refueling.
Building on their previous research on environmental life cycle assessment (LCA) for heavy-duty trucks, the researchers will conduct a social LCA analysis to assess the social impacts of battery-electric and fuel cell trucks.
