Energy-based FCEV Optimization Services: Toward Greener Transportation
Fuel cell electric vehicles (FCEVs) represent a significant advancement in the effort of the automotive industry to improve energy efficiency within transportation by converting chemical energy from hydrogen fuel into electrical energy, thereby offering a more sustainable alternative to fossil fuels. However, while this inherent clean energy process brings FCEVs to the forefront of future green mobility strategies, their widespread adoption still faces several challenges regarding effective energy optimization and fuel cell lifetime span. For this purpose, the present research study analyzes key hydrogen vehicle technologies and sets the basis for the implementation of two novel energy-based FCEV optimization services, namely, the driving behavior optimization and the refueling automation, leveraging real-time data along with unsupervised and supervised machine learning (ML) algorithms to improve hydrogen fuel efficiency, driving range and fuel cell durability. By integrating advanced artificial intelligence (AI) technologies, a holistic approach to overcome operational challenges is offered, ultimately maximizing the potential of hydrogen-powered transportation.
Authors
- Georgios Spanos (ORCID: https://orcid.org/0000-0002-2804-385X)
- Antonios Lalas (ORCID: https://orcid.org/0000-0002-5337-161X)
- Konstantinos Votis (ORCID: https://orcid.org/0000-0001-6381-8326)
- Sofia Polymeni (ORCID: https://orcid.org/0000-0002-9829-0194)
- Vasileios Pitsiavas
- Dimitrios Tzovaras
Institutions
- Information Technologies Institute (GR)
Publication Details
- Journal
- Transportation research procedia
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1016/j.trpro.2025.04.032
- Primary Topic
- Vehicle emissions and performance
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- FP7 Coordination of Research Activities