Researchers present a simulation-based quasi-statistical approach to estimate electric vehicle energy consumption under various on-road vehicle operating conditions.
This research will address policy-relevant questions by investigating cost-efficient ways to implement a RUC, evaluating the equity impacts of RUC, and quantifying factors that influence household’s PEV adoption decisions.
This project will address the issues of freight decarbonization and supply chain resiliency by designing electric truck fleet management strategies that consider limited charging availability for electric vehicles, respond to electricity grid uncertainties, and analyze the constraints of long-haul and short-haul operations with electric trucks.
This research explores the range of tangible benefits that the implementation of transportation electrification programs can achieve for disadvantaged communities.
This research will improve long-term sustainability by identifying how and why (or why not) transportation electrification (TE) projects align with regional and local transportation goals. The research will result in a deep dive case study that can serve as a template for evaluating future TE expenditures with respect to identifying and quantifying disadvantaged community benefits.
This study identifies heavily-trafficked freight truck routes of optimal distances in Georgia and quantifies electrification benefits for fleets operating on these corridors by integrating outputs from MOVES Matrix, the Argonne National Laboratory’s GREET Model, the Georgia Tech Fuel and Emissions Calculator (FEC), and other models into a web-based tool.
This project utilizes the Department of Energy's Systems and Modeling for Accelerated Research in Transportation (SMART) workflow to evaluate potential outcomes of electrification policies, specifically for transit and rideshare systems. This will be accomplished by harnessing a large-scale agent-based activity-based transportation modeling tool designed for the Houston Metropolitan Area.
In the research, smart charging will be explored in the larger context of electric vehicle fleets carrying freight and/or people to assess its potential to again decrease charging costs, increase carbon-free energy usage, decrease spatially-concentrated peak demands on the grid, and lower infrastructure investment.
