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Dynamic EV Battery Health Recommendations

Authors:

Andreas BerlAuthors Info & Claims

e-Energy '18: Proceedings of the Ninth International Conference on Future Energy Systems

Pages 586 - 592

https://doi.org/10.1145/3208903.3213896

Published: 12 June 2018 Publication History

Abstract

Prolonging the lifetime of batteries in Electric Vehicles (EVs) becomes a more and more important issue for private users and fleet operators. In addition to the environmental point of view, a better battery health results in less cost, higher battery capacities and higher performance. To achieve this, the EV drivers or the fleet operators need to get proper information, which kind of actions will increase or decrease the batteries health. To this point, various tips and recommendations exist distributed over literature. Unfortunately, those kind of recommendations are hard to follow in the day-to-day routine. This paper suggests so called dynamic recommendations for battery health that are able to advise the user in specific situations with respect to battery use. Recommendations from literature are broken down into a list, which can be automatically computed. Recommendations will then be dynamically created in the current context of the EV and displayed to the user just in time.

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Cited By

Pongchanchai NTumma LNilsson MObaid M(2024)A User-Centred Representation of Battery Health in Electric VehiclesAdjunct Proceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3641308.3685042(166-171)Online publication date: 22-Sep-2024
https://dl.acm.org/doi/10.1145/3641308.3685042
Carvalhosa SFerreira JAraújo R(2024)Electric Vehicle Charging Method for Existing Residential CondominiumsIEEE Access10.1109/ACCESS.2024.349137912(166537-166552)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3491379
S VChe HSelvaraj JTey KLee JShareef HErrouissi R(2024)State of Health (SoH) estimation methods for second life lithium-ion battery—Review and challengesApplied Energy10.1016/j.apenergy.2024.123542369(123542)Online publication date: Sep-2024
https://doi.org/10.1016/j.apenergy.2024.123542
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Index Terms

Dynamic EV Battery Health Recommendations

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Published In

cover image ACM Conferences

e-Energy '18: Proceedings of the Ninth International Conference on Future Energy Systems

June 2018

657 pages

ISBN:9781450357678

DOI:10.1145/3208903

Copyright © 2018 Owner/Author.

This work is licensed under a Creative Commons Attribution International 4.0 License.

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SIGCOMM: ACM Special Interest Group on Data Communication

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 June 2018

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Horizon 2020 Framework Programme

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e-Energy '18

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SIGCOMM

e-Energy '18: The Ninth International Conference on Future Energy Systems

June 12 - 15, 2018

Karlsruhe, Germany

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Overall Acceptance Rate 160 of 446 submissions, 36%

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E-Energy '25

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The 16th ACM International Conference on Future and Sustainable Energy Systems

June 17 - 20, 2025

Rotterdam , Netherlands

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Cited By

Pongchanchai NTumma LNilsson MObaid M(2024)A User-Centred Representation of Battery Health in Electric VehiclesAdjunct Proceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3641308.3685042(166-171)Online publication date: 22-Sep-2024
https://dl.acm.org/doi/10.1145/3641308.3685042
Carvalhosa SFerreira JAraújo R(2024)Electric Vehicle Charging Method for Existing Residential CondominiumsIEEE Access10.1109/ACCESS.2024.349137912(166537-166552)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3491379
S VChe HSelvaraj JTey KLee JShareef HErrouissi R(2024)State of Health (SoH) estimation methods for second life lithium-ion battery—Review and challengesApplied Energy10.1016/j.apenergy.2024.123542369(123542)Online publication date: Sep-2024
https://doi.org/10.1016/j.apenergy.2024.123542
Montoya‐Bedoya SGarcia‐Tamayo ERohrbach DGaviria‐Cardona JMartinez‐Tejada HPlanden BHowey DFlorez WValencia RBernal M(2024)Quantitative Ultrasound Spectroscopy for Screening Cylindrical Lithium‐Ion Batteries for Second‐Life ApplicationsBatteries & Supercaps10.1002/batt.2024000027:5Online publication date: 3-Apr-2024
https://doi.org/10.1002/batt.202400002
Krot KIskierka GPoskart BGola A(2022)Predictive Monitoring System for Autonomous Mobile Robots Battery Management Using the Industrial Internet of Things TechnologyMaterials10.3390/ma1519656115:19(6561)Online publication date: 21-Sep-2022
https://doi.org/10.3390/ma15196561
Bodenschatz NEider MBerl A(2021)Challenges and Requirements of Electric Vehicle Fleet Charging at Company Parking Sites2021 11th International Conference on Advanced Computer Information Technologies (ACIT)10.1109/ACIT52158.2021.9548563(623-628)Online publication date: 15-Sep-2021
https://doi.org/10.1109/ACIT52158.2021.9548563
Pattnaik SRay O(2021)Battery Replacement Schedule Analysis for Dissimilar SOC-Type Multi-cell Configuration Under Battery Swap Charging SchemeProceedings of Symposium on Power Electronic and Renewable Energy Systems Control10.1007/978-981-16-1978-6_20(229-238)Online publication date: 10-Jul-2021
https://doi.org/10.1007/978-981-16-1978-6_20
Pelayo JTan SYu PMagwili GCruz F(2020)Simulated Solar Assisted Battery Management System with Fuzzy Temperature Control, Flyback Converter Active Cell Balancing Circuit and Coulomb Counting SoC Estimation Method using MATLAB Simulink2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)10.1109/HNICEM51456.2020.9400158(1-6)Online publication date: 3-Dec-2020
https://doi.org/10.1109/HNICEM51456.2020.9400158
Eider MBerl A(2020)Requirements for Prescriptive Recommender Systems Extending the Lifetime of EV Batteries2020 10th International Conference on Advanced Computer Information Technologies (ACIT)10.1109/ACIT49673.2020.9209011(412-417)Online publication date: Sep-2020
https://doi.org/10.1109/ACIT49673.2020.9209011

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