TY - GEN
T1 - EV Battery Degradation
T2 - 5th EAI International Conference on Intelligent Transport Systems, INTSYS 2021
AU - Rodrigues, Rui
AU - Albuquerque, Vitória
AU - Ferreira, Joao C.
AU - Dias, Miguel Sales
N1 - Rodrigues, R., Albuquerque, V., Ferreira, J. C., & Dias, M. S. (2022). EV Battery Degradation: A Data Mining Approach. In A. L. Martins, J. C. Ferreira, & A. Kocian (Eds.), Intelligent Transport Systems: 5th EAI International Conference, INTSYS 2021, Proceedings (pp. 177-191). (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 426 LNICST). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-97603-3_13 ------------------- Funding Information:
This study was performed in the scope of ISCTE collaboration with Santos e Vale, who financed the research.
Publisher Copyright:
© 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
PY - 2022/3/12
Y1 - 2022/3/12
N2 - 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.
AB - 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.
KW - Behavior
KW - Charging process
KW - Electric vehicles
UR - http://www.scopus.com/inward/record.url?scp=85126946062&partnerID=8YFLogxK
UR - https://www.webofscience.com/wos/woscc/full-record/WOS:000784754900013
U2 - 10.1007/978-3-030-97603-3_13
DO - 10.1007/978-3-030-97603-3_13
M3 - Conference contribution
AN - SCOPUS:85126946062
SN - 9783030976026
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
SP - 177
EP - 191
BT - Intelligent Transport Systems
A2 - Martins, Ana Lúcia
A2 - Ferreira, Joao C
A2 - Kocian, Alexander
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 24 November 2021 through 26 November 2021
ER -
