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.

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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

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Energy-based FCEV Optimization Services: Toward Greener Transportation

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Energy-based FCEV Optimization Services: Toward Greener Transportation

Georgios Spanos, Antonios Lalas, Konstantinos Votis, Sofia Polymeni, Vasileios Pitsiavas, Dimitrios Tzovaras
article en

Abstract

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.

Transportation research procediaVol. 86
Information Technologies Institute (GR)
FP7 Coordination of Research Activities
Openalex Percentile: Top 90%
Vehicle emissions and performance
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