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Volume 13
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Article

Data-Driven Propulsion Load Optimization: Reducing Fuel Consumption and Greenhouse Gas Emissions in Double-Ended Ferries

by
Andres Laasma
1,2,*,
Deniece M. Aiken
2,
Kadi Kasepõld
2,
Olli-Pekka Hilmola
2,3 and
Ulla Pirita Tapaninen
2
1
Estonian State Fleet, Lume 9, 10416 Tallinn, Estonia
2
Estonian Maritime Academy, Tallinn University of Technology, Kopli 101, 11712 Tallinn, Estonia
3
Department of Industrial Engineering and Management, University of Gävle, SE-801 76 Gävle, Sweden
*
Author to whom correspondence should be addressed.
J. Mar. Sci. Eng. 2025, 13(4), 688; https://doi.org/10.3390/jmse13040688
Submission received: 2 March 2025 / Revised: 26 March 2025 / Accepted: 26 March 2025 / Published: 28 March 2025
(This article belongs to the Special Issue Performance and Emission Characteristics of Marine Engines)
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Abstract

As the focus on climate action and sustainable development of the shipping industry intensifies, the maritime sector has intensified its focus on decarbonization. Although the ferry sector accounts for a small part of the global fleet, it plays a crucial role in specific regions. This study examines data from an energy monitoring system installed on a double-ended Estonian ferry over the period from 2022 to 2024. The empirical results clearly show that targeted adjustments can lead to substantial fuel consumption reductions as the optimal operation of the vessel requires equal power from the aft and fore engines particularly when operating under cold or icy conditions. Additionally, the research finds that real-time energy monitoring together with integrating environmental factors supports energy efficiency and fulfilling regulatory requirements. The analysis reveals that environmental corrections and balanced decision-making can generate fuel savings and extended emission reductions. The suggested framework offers ferry operators practical and economical ways of meeting sustainability requirements.
Keywords: maritime transportation; energy efficiency; GHG emissions; ferry operations; data-driven optimization; propulsion load maritime transportation; energy efficiency; GHG emissions; ferry operations; data-driven optimization; propulsion load

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MDPI and ACS Style

Laasma, A.; Aiken, D.M.; Kasepõld, K.; Hilmola, O.-P.; Tapaninen, U.P. Data-Driven Propulsion Load Optimization: Reducing Fuel Consumption and Greenhouse Gas Emissions in Double-Ended Ferries. J. Mar. Sci. Eng. 2025, 13, 688. https://doi.org/10.3390/jmse13040688

AMA Style

Laasma A, Aiken DM, Kasepõld K, Hilmola O-P, Tapaninen UP. Data-Driven Propulsion Load Optimization: Reducing Fuel Consumption and Greenhouse Gas Emissions in Double-Ended Ferries. Journal of Marine Science and Engineering. 2025; 13(4):688. https://doi.org/10.3390/jmse13040688

Chicago/Turabian Style

Laasma, Andres, Deniece M. Aiken, Kadi Kasepõld, Olli-Pekka Hilmola, and Ulla Pirita Tapaninen. 2025. "Data-Driven Propulsion Load Optimization: Reducing Fuel Consumption and Greenhouse Gas Emissions in Double-Ended Ferries" Journal of Marine Science and Engineering 13, no. 4: 688. https://doi.org/10.3390/jmse13040688

APA Style

Laasma, A., Aiken, D. M., Kasepõld, K., Hilmola, O.-P., & Tapaninen, U. P. (2025). Data-Driven Propulsion Load Optimization: Reducing Fuel Consumption and Greenhouse Gas Emissions in Double-Ended Ferries. Journal of Marine Science and Engineering, 13(4), 688. https://doi.org/10.3390/jmse13040688

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