EV Battery Degradation: A Data Mining Approach

Rui Rodrigues, Vitória Albuquerque, Joao C. Ferreira, Miguel Sales Dias

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationIntelligent Transport Systems
Subtitle of host publication 5th EAI International Conference, INTSYS 2021, Proceedings
EditorsAna Lúcia Martins, Joao C Ferreira, Alexander Kocian
PublisherSpringer Science and Business Media Deutschland GmbH
Pages177-191
Number of pages15
ISBN (Print)9783030976026
DOIs
Publication statusPublished - 12 Mar 2022
Event5th EAI International Conference on Intelligent Transport Systems, INTSYS 2021 - Virtual, Online
Duration: 24 Nov 202126 Nov 2021

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume426 LNICST
ISSN (Print)1867-8211
ISSN (Electronic)1867-822X

Conference

Conference5th EAI International Conference on Intelligent Transport Systems, INTSYS 2021
CityVirtual, Online
Period24/11/2126/11/21

Keywords

  • Behavior
  • Charging process
  • Electric vehicles

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