State Model and Energy Consumption Analysis based on Automotive Lighting Signals

Osman Aksu, Xinyi Liu, Michael Schmid, Florian Bierwirth, Mišel Radosavac, Hans Georg Herzog

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

Abstract

With the development of electric vehicles, motor vehicles have gradually shifted from being dominated by mechanical functions to relying on electrical functions for control and operation. Additionally new features that improve driving experience have become research focus. Therefore, creating a mission profile and challenging the the real maximum energy consumption required for vehicle functions, is an enabler for new vehicle functions. This paper suggests a state model based on data collected from the Controller Area Network bus (CAN) for automotive lighting signals and conducts an in-depth analysis of their impact in combination with their analogue data on energy consumption. A vehicle state-dependent current requirement is obtained by examining the dynamic changes in current signals and correlating them with various lighting functions. The resulting pattern of regular current fluctuations provides correlations to the vehicles' real energy consumption. This research is of significant importance within the context of future electric vehicle energy consumption.

Original languageEnglish
Title of host publication2024 IEEE 100th Vehicular Technology Conference, VTC 2024-Fall - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331517786
DOIs
StatePublished - 2024
Event100th IEEE Vehicular Technology Conference, VTC 2024-Fall - Washington, United States
Duration: 7 Oct 202410 Oct 2024

Publication series

NameIEEE Vehicular Technology Conference
ISSN (Print)1550-2252

Conference

Conference100th IEEE Vehicular Technology Conference, VTC 2024-Fall
Country/TerritoryUnited States
CityWashington
Period7/10/2410/10/24

Keywords

  • analogue data
  • CAN data
  • dynamic measurement data
  • light control
  • state model

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