@inproceedings{97d5e2a3ed1747a6bc8781317cd99985,
title = "State Model and Energy Consumption Analysis based on Automotive Lighting Signals",
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.",
keywords = "analogue data, CAN data, dynamic measurement data, light control, state model",
author = "Osman Aksu and Xinyi Liu and Michael Schmid and Florian Bierwirth and Mi{\v s}el Radosavac and Herzog, {Hans Georg}",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 100th IEEE Vehicular Technology Conference, VTC 2024-Fall ; Conference date: 07-10-2024 Through 10-10-2024",
year = "2024",
doi = "10.1109/VTC2024-Fall63153.2024.10757602",
language = "English",
series = "IEEE Vehicular Technology Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2024 IEEE 100th Vehicular Technology Conference, VTC 2024-Fall - Proceedings",
}