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Context-aware recommendations for extended electric vehicle battery lifetime.

Authors :
Eider, Markus
Sick, Bernhard
Berl, Andreas
Source :
Sustainable Computing: Informatics & Systems; Jan2023, Vol. 37, pN.PAG-N.PAG, 1p
Publication Year :
2023

Abstract

Electric vehicles are a means of reducing CO 2 emissions in transportation. However, the sustainability of electric vehicle batteries is affected by battery health degradation, which decreases their overall lifetime. This results in a substantial amount of depleted batteries due to replacements. Users have a major impact on battery health degradation through their actions while handling electric vehicles, such as the use of fast charging. To mitigate this problem, this article presents a methodology to generate user guidance for battery-friendly actions in the upcoming use. Therefore, we first identify general recommendations from related work and combine them with the vehicle context in order to define context-aware recommendations in the form of if–then rules. These context-aware recommendations are then used to generate user advice. Second, the article covers how to predict the vehicle context in order to determine necessary recommendations. Third, a prescriptive recommendation system architecture is proposed, which takes vehicle context information, and produces user guidance. Finally, we test the proposed architecture using fuzzy logic as decision system. Overall, the architecture provides satisfactory user advice. • Drivers influence the degradation rate of electric vehicle batteries. • Context-aware guidance for battery-friendly electric vehicle operation. • Prescriptive recommender system architecture to generate guidance. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22105379
Volume :
37
Database :
Supplemental Index
Journal :
Sustainable Computing: Informatics & Systems
Publication Type :
Academic Journal
Accession number :
161488683
Full Text :
https://doi.org/10.1016/j.suscom.2022.100845