Project Grant 2340194
- This federal Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) provides $600,000 in funding to the Texas A&M Engineering Experiment Station (Tees) to research and develop novel robotic solutions for repairing aged electric vehicle (EV) batteries. The project, titled "BRITE PIVOT: DEEP ROBOTIC EV BATTERY REPAIR: AN LLM-POWERED TASK-MOTION-MANIPULATION PLANNING FRAMEWORK," aims to leverage emerging artificial intelligence (AI)...
- This National Science Foundation (NSF) Integrative Activities (CFDA 47.083) project grant award of $279,105 to the University of Alabama in Huntsville (UAH) aims to develop transformative solutions for enhancing the capabilities of electric vehicle battery management systems. The key products to be delivered include: An interconnected electro-thermal-aging model of a lithium-ion battery pack to better understand the interplay between electrical, thermal, and aging behavior and their impact on...
- This $300,000 Project Grant awarded by the National Science Foundation's Engineering program (CFDA 47.041) aims to develop batteryless technology for Internet of Things (IoT) devices, particularly in wearable applications such as fitness trackers, smartwatches, and medical devices. The project will integrate artificial intelligence (AI) and deep learning techniques to harness the potential of batteryless sensors for personalized data analytics. Key objectives include: Developing new deep...
- This Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) provides $467,544 to Brown University to conduct research and development on rational design of fast-charging, composite electrodes with next-generation battery materials and complex architectures. The goal is to develop safer, cheaper, and more efficient battery technologies to support widespread adoption of electric vehicles. The 3-year project, running from October 1, 2025 to September 30,...
- This $200,000 Project Grant awarded by the National Science Foundation (NSF) Engineering program (CFDA 47.041) aims to utilize ultrasonic guided waves to study lithium-ion battery degradation and develop robust algorithms for accurately predicting the state of charge, state of health, and remaining useful life of batteries in real-time. The research project, conducted by South Dakota State University (SDSU), is focused on addressing the challenges posed by natural battery degradation, which...
- This $170,000 Project Grant awarded by the National Science Foundation (NSF) Engineering Program (CFDA 47.041) aims to uncover the relationship between liquid electrolytes and battery performance, which is crucial for developing next-generation rechargeable batteries. The research team at the University of Illinois will systematically vary electrolyte composition and concentration to identify optimal solutions, leveraging high-throughput characterization, computational simulations, and machine...
- This $268,134 project grant, awarded by the National Science Foundation's (NSF) Engineering program (CFDA 47.041), aims to develop new chemical compounds called "biphasic charge carriers" that can store electric power for use in redox flow batteries (RFBs). The research will focus on linking the fundamental chemical properties of these charge carriers to their function in small-scale working batteries, with the goal of developing design principles for a new generation of batteries...
- This $370,413 Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) supports research to explore the effects of molecular crowding on zinc-ion electrolytes for improving the performance and longevity of zinc-ion batteries. The University of Texas at Dallas will lead this 3-year project from September 2025 to August 2028. The research aims to establish a mechanistic understanding of how adding non-reactive crowding agents to the electrolyte can tune...
- This NSF Project Grant for $320,000.00, awarded to Oakland University and running from May 2025 to April 2028, aims to advance sustainable electrification systems through the development of a novel estimation and monitoring framework that requires fewer sensors for repurposing retired electric vehicle batteries. The key objectives are to: (1) develop a dense extended Kalman filter to simultaneously estimate parameters for a large number of connected cells without requiring sensor measurements...
- This Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) provides $549,771 to the University of Houston System to research the formation of pore-free interlayers for solid-state lithium metal batteries. The project aims to address interfacial challenges in these batteries by focusing on the development of a metal-carbon mixed ionic-electronic conductor (C-MIEC) interlayer material. The research will combine automated in situ diagnostic technologies,...
This $415,746 federal Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) to Texas Tech University System supports the development of intelligent battery management systems with novel reinforcement learning and machine learning methods. The key products and services to be delivered include: Developing deep reinforcement learning-based methods to enable safe and adaptive fast-charging protocols for electric vehicle batteries. Creating efficient and physics-informed transformer-based battery health prognostics models to accurately estimate capacity and predict battery lifetime, while considering cell-to-cell inconsistencies within battery packs. Validating the proposed battery management technologies using both open-source simulation platforms and experimental battery testbeds. Making the software implementations of these algorithms publicly available to advance research and education in this field. The award also includes components to integrate the research findings into the university's chemical engineering curriculum and to conduct K-12 and undergraduate student outreach to cultivate a "data thinking" mindset. The project will be conducted over a 5-year period from February 2024 to January 2029.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $415.7k | 1/8/24 |