Impact Evaluation of Driving Style on Electric Vehicle Battery based on Field Testing Result

Ka Seng Chou, Davide Aguiari, Rita Tse, Su Kit Tang, Giovanni Pau

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

2 Citations (Scopus)

Abstract

Monitoring electric vehicles' battery status and forecasting their state of health is still an open challenge. To determine how and why a battery degrades over time, we have extensively monitored a Nissan Leaf's battery pack for more than one year. Collecting more than 4.5 million samples via a custom monitoring connected device to investigate how different driving behaviors affect battery aging. In addition, the best driving behaviors based on the battery's optimal temperature are revealed, including speed, acceleration and brake pedal pressure, and horsepower.

Original languageEnglish
Title of host publication2023 IEEE 20th Consumer Communications and Networking Conference, CCNC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1143-1146
Number of pages4
ISBN (Electronic)9781665497343
DOIs
Publication statusPublished - 2023
Event20th IEEE Consumer Communications and Networking Conference, CCNC 2023 - Las Vegas, United States
Duration: 8 Jan 202311 Jan 2023

Publication series

NameProceedings - IEEE Consumer Communications and Networking Conference, CCNC
Volume2023-January
ISSN (Print)2331-9860

Conference

Conference20th IEEE Consumer Communications and Networking Conference, CCNC 2023
Country/TerritoryUnited States
CityLas Vegas
Period8/01/2311/01/23

Keywords

  • Battery Aging
  • Driving Behaviour
  • Electric Vehicle
  • Lithium Battery
  • SOH

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