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EV Battery Degradation: A Data Mining Approach

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Intelligent Transport Systems (INTSYS 2021)

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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.

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Acknowledgments

This study was performed in the scope of ISCTE collaboration with Santos e Vale, who financed the research.

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Authors and Affiliations

  1. ISCTE - University Institute of Lisbon, 1649-026, Lisbon, Portugal

    Rui Rodrigues, Joao C Ferreira & Miguel Sales Dias

  2. NOVA Information Management School (NOVA IMS), Campus de Campolide, Universidade Nova de Lisboa, 1070-312, Lisbon, Portugal

    Vitória Albuquerque

Authors
  1. Rui Rodrigues
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  2. Vitória Albuquerque
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  3. Joao C Ferreira
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  4. Miguel Sales Dias
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Corresponding author

Correspondence to Rui Rodrigues .

Editor information

Editors and Affiliations

  1. Lisbon University Institute, Lisbon, Portugal

    Ana Lúcia Martins

  2. Lisbon University Institute, Lisbon, Portugal

    Joao C Ferreira

  3. University of Pisa, Pisa, Italy

    Alexander Kocian

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Rodrigues, R., Albuquerque, V., Ferreira, J.C., Dias, M.S. (2022). EV Battery Degradation: A Data Mining Approach. In: Martins, A.L., Ferreira, J.C., Kocian, A. (eds) Intelligent Transport Systems. INTSYS 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 426. Springer, Cham. https://doi.org/10.1007/978-3-030-97603-3_13

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  • DOI: https://doi.org/10.1007/978-3-030-97603-3_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-97602-6

  • Online ISBN: 978-3-030-97603-3

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