Multi-Partner Project: Electric Vehicle Data Acquisition and Valorisation: A Perspective from the OPEVA Project


Kanak A., Ergün S., Arif I., Atalay A. S., Inanç S. E., Herkiloǧlu O., ...More

2025 Design, Automation and Test in Europe Conference, DATE 2025, Lyon, France, 31 March - 02 April 2025, (Full Text) identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.23919/date64628.2025.10992740
  • City: Lyon
  • Country: France
  • Keywords: cloud computing, Electric Vehicles, Federated Learning, Internet of Things, Machine Learning
  • Eskisehir Osmangazi University Affiliated: Yes

Abstract

The OPtimization of Electric Vehicle Autonomy (OPEVA) project enhances data aggregation for Electric Vehicles (EVs) by collecting critical real-time data (i.e., vehicle performance, battery health, charging behaviours) through heterogeneous data acquisition devices built on robust HW and integrated with Internet of Things (IoT) protocols. By combining internal sensor data and driver-specific behaviours with external information (e.g., road conditions, charging station availability), OPEVA maximizes vehicles performance, establishing secure and seamless data communication between EVs and the infrastructure, and using IoT and cloud computing tools alongside Vehicle-to-Everything (V2X) devices and networks. This paper focuses on the extensible data model ensuring semantic data integrity considering in- and out-vehicle factors, presenting data acquisition solutions dealing with OPEVA's semantic data model and their use in various Artificial Intelligence (AI)-powered use cases (e.g., range prediction, route optimization, battery management).