This Project Grant, awarded by the National Science Foundation (NSF) under the Engineering program (CFDA 47.041), provides $195,769 to Tennessee Technological University (Tennessee Tech) to develop scalable models and forecasting tools for planning and operating an electrified transportation network (ETN). The key products to be delivered include: A scalable travel motif-based electric vehicle (EV) data generation model that uses publicly available data to simulate individual EV travel patterns and system-level demands. A recurrent-graph convolutional network-based learning model for forecasting spatiotemporal EV demand to support resource planning for the ETN. A land use and land change analysis model to predict population growth and EV distribution changes, informing long-term ETN expansion strategies. The project aims to address limitations in EV data availability that hinder accurate ETN planning, including EVCS deployment, network hotspot identification, and road expansion. The interdisciplinary research is expected to enhance scientific and technological understanding for data-driven EV operation and infrastructure planning, supporting the National Electric Vehicle Infrastructure (NEVI) program's goal of promoting net-zero transportation in the United States.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $195.8k | 5/28/24 |