Research Article
EV Battery Degradation: A Data Mining Approach
@INPROCEEDINGS{10.1007/978-3-030-97603-3_13, author={Rui Rodrigues and Vit\^{o}ria Albuquerque and Joao C Ferreira and Miguel Sales Dias}, title={EV Battery Degradation: A Data Mining Approach}, proceedings={Intelligent Transport Systems. 5th EAI International Conference, INTSYS 2021, Virtual Event, November 24-26, 2021, Proceedings}, proceedings_a={INTSYS}, year={2022}, month={3}, keywords={Electric vehicles Charging process Behavior}, doi={10.1007/978-3-030-97603-3_13} }- Rui Rodrigues
Vitória Albuquerque
Joao C Ferreira
Miguel Sales Dias
Year: 2022
EV Battery Degradation: A Data Mining Approach
INTSYS
Springer
DOI: 10.1007/978-3-030-97603-3_13
Abstract
The increase in greenhouse gas emissions into the atmosphere, and their adverse effects on the environment, has prompted the search for alternative energy sources to fossil fuels. One of the solutions gaining ground is the electrification of various human activities, such as the transport sector. This trend has fueled a growing need for electrical energy storage in lithium-ion batteries. Precisely knowing the degree of degradation that this type of battery accumulates over its useful life is necessary to bring economic benefits, both for companies and citizens. This paper aims to answer the current need by proposing a research question about electric motor vehicles. It focuses on habits EV owners practice, which could harm the battery life. This paper seeks to answer this question using a data science methodology. The results allowed us to conclude that all other factors had a marginal effect on the vehicles’ autonomy decrease except for the car year. The biggest obstacle encountered in adopting electric vehicles was the insufficient coverage of the charging stations network.
