What is it about?
In this publication, we decided to study how Artificial Intelligence could help in estimating the State of Health of batteries. There are various AI methods that exist but seldom are those that are applied to the specific methodologies of batteries. Hence, we focused of testing some AI methods that are supposed to present the best results in order to classify if a battery is at its end of life or not.
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Why is it important?
As of now, most of the vehicles used worldwide are using petrol for propulsion. However, there is a huge change that is appearing regarding that, especially with the appearance of electric vehicles. Being able to predict the state of batteries inside these vehicles could allow to perform predictive maintenance in order to maximize the use of these batteries.
Perspectives
For this research, the perspectives are focused on doing our own test benches in order to have a complete control over the inputs and outputs. It will allow the use of better algorithms, especially ones based on regression.
Léo Challier
Read the Original
This page is a summary of: Exploratory study of battery aging analysis with machine learning models to complete multi-physical ones for more adaptable systems, March 2022, ACM (Association for Computing Machinery),
DOI: 10.1145/3529399.3529402.
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