Project Grant 2431969
Award Date
6/15/25
Completion Date
5/31/27
Dollars Obligated
$550K
Federal Agency
National Science Foundation
Federal Grant Program
47.084
Assistance Type
Project Grant
Place of Performance
Fayetteville, AR 72701, USA
Similar Awards
This $1,000,000 federal Project Grant award from the National Science Foundation (NSF) Technology, Innovation, and Partnerships (TIP) program (CFDA 47.084) is funding the development of a smart sensor system capable of detecting anomalies, locating issues, and diagnosing problems in electrical devices and networks. Led by the University of Georgia Research Foundation, the project aims to enhance the reliability and security of electrical infrastructure in buildings, manufacturing facilities, and...
This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) provides $199,998 to Michigan Technological University to develop advanced real-time signal processing capabilities for fault diagnosis in next-generation power grids. The project aims to create a novel wavelet transform theory and machine learning-based framework to rapidly detect, classify, and predict faults in complex AC and DC power systems, including those with high penetration of...
This $274,995 federal Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) aims to develop new techniques for fault detection in inverter-dominated power systems. The project, titled "Collaborative Research: Auxiliary Signal-Based Fault Detection in Inverter-Dominated Power Systems," will create innovative fault detection schemes that leverage auxiliary signals injected by inverters to distinguish normal operation from faults. The research will...
This National Science Foundation Project Grant of $449,999 will support the development of an innovative and high power-density traction inverter for electric vehicles through July 2025. Funded by the NSF Directorate for Engineering under the CFDA 47.041 Engineering program, this award aims to design an electro-thermally integrated traction inverter utilizing wide bandgap silicon carbide power semiconductor devices. Led by the University of Maryland, College Park with the University System of...
This National Science Foundation (NSF) Integrative Activities (CFDA# 47.083) Project Grant award provides $300,000 to the University of Arkansas to enhance the power density and operating temperature range of traction inverters for electric vehicles (EVs) through the use of gallium oxide-based power modules. The key objectives are to: 1) innovate power module packaging techniques to optimize thermal resistances, minimize parasitic inductances, and enhance high-temperature operation; 2) explore...
This $275,000 Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) aims to develop new techniques for fault detection in inverter-dominated power systems. The project will design auxiliary signal-based fault detection schemes to improve reliability in power grids with high penetration of renewable energy resources like wind and solar, which can pose challenges for conventional detection methods. The research will characterize the necessary auxiliary...
This National Science Foundation Project Grant of $400,001 awarded to Mississippi State University on August 15, 2022 will fund research and development of degradation-aware self-healing control technologies for power electronics systems through July 31, 2025. Under the NSF Engineering program (CFDA 47.041), the university will develop data-driven models using generative adversarial networks to more accurately predict the remaining useful lifetime of wide bandgap power switches under diverse...
This National Science Foundation (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) Project Grant for $274,944 awarded to Valcon Labs Inc. aims to develop self-healing, fault-tolerant power electronics for urban air mobility (UAM) applications. The key objectives are to improve fault tolerance in the event of battery or motor failure, explore machine learning techniques for DC/AC inverters and AC/DC chargers, and study the impact of the proposed self-healing modular power electronics...
This $199,106 Project Grant awarded by the National Science Foundation's Engineering program (CFDA 47.041) supports research to develop a scalable predictive modeling framework that leverages sensor data and failure event information to enable accurate, privacy-preserving system failure prognosis. The key objectives are to enhance failure prediction accuracy through federated survival analysis, facilitate adaptive failure predictions using Bayesian methods and functional principal component...
This National Science Foundation (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) Project Grant award of $274,951 to Parthian Battery Solutions LLC will develop a novel technology to rapidly and accurately assess the state of health of second-life lithium-ion batteries. The technology will utilize advanced battery modeling and data analytics to determine the overall battery health beyond just capacity degradation, enabling more informed decision-making for repurposing retired...