Artificial Neural Networks for Predicting Battery SOH
General description of the project
Abstract:
This research focuses on applying machine learning (ML) to evaluate the State of Health (SOH) of re-chargeable batteries, which are widely used in renewable energy related applications. Battery SOH will be predicted and compared among neural networks. With our Electric Flight Vehicle (EFV) dataset, we were able to extract a substantial training and testing dataset to be used. The Keras Sequential Model is the first method being tested.
Technologies
Keras API, Python
Explain project results
I worked with a Hispanic student.
Why it should be considered best practice?
The research is, in a way, a replication of previously done research. I am testing that the results of other researchers is reproducible.
Highlights of your proposed presentation
Learned about how artificial neural networks worked and which ones are best for different applications.
The Evaluation Committee will evaluate submitted proposals based on the following criteria. Each area will be rated on a scale from 1 to 7 (1= non-satisfactory; 7 =outstanding), for a maximum of 63 points.