Nithin Jakrebet
Computer science
Hometown: Phoenix, Arizona, United States
Graduation date: Spring 2025
Additional details: Honors student
FURI | Spring 2024
Lithium-ion Battery Degradation Machine Learning Model
The objective of this study is to use impedance data to develop a machine-learning model capable of accurately predicting the state of health of lithium-ion batteries. By analyzing the relationship between impedance characteristics and battery health, the model demonstrates a new, noninvasive approach to testing and extending battery life and enhancing reliability. The findings highlight the potential for improved efficiency of battery usage. Future work should focus on continuing to improve the accuracy through increased data collection and possibly applying different machine learning algorithms.
Mentor: Nick Rolston
It’s hip to be square.
Students presenting projects at the Fulton Forge Student Research Expo are encouraged to download this personal QR code and include it within your poster. This allows expo attendees to explore more about your project and about you in the future.
Right click the image to save it to your computer.