Leveraging Advanced Machine Learning Algorithms for Energy Efficiency and Carbon Footprint Reduction in Diesel Engines

Emrah Arda; Mehmet Demir; Samet Çelebi; Üsame Demir; Ömer Seçgin

doi:10.30939/ijastech..1896122

Leveraging Advanced Machine Learning Algorithms for Energy Efficiency and Carbon Footprint Reduction in Diesel Engines

Abstract

In this study, machine learning-based models were employed to estimate brake-specific fuel consumption (BSFC) using the data derived from 300 experimental engine tests conducted under varying loads, EGR ratios, and fuel combinations. Eleven alternative algorithms, including AdaBoost, Gradient Boosting, Random Forest, SVM, and Neural Network, were evaluated using datasets derived from real engine data. Statistical tools such as the R² coefficient and Mean Square Error (MSE) were utilized to assess the performance of the models. The best results were derived using Gradient Boosting (R² = 0.9998), AdaBoost (R² = 0.9998), and Random Forest (R² = 0.9997). In the prediction process of the Gradient Boosting model, the minimum absolute error was found to be 0.0000000, and the maximum absolute error was found to be 0.000002. The model's prediction accuracy ranges from 98.30% to 99.39%. This degree of accuracy demonstrates that fuel consumption can be predicted from engine data alone, without installing fuel-measurement equipment. The model's forecasting performance has been examined by analyzing the most and least successful examples. The results simplify fuel-consumption measurement procedures, provide the infrastructure for AI-supported test systems, and reduce time and labor. In this respect, the study significantly advances the digitization of engine testing in both academia and industry.

Keywords

References

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Details

Primary Language

English

Subjects

Internal Combustion Engines, Automotive Combustion and Fuel Engineering, Automotive Engineering (Other)

Journal Section

Research Article

Authors

Emrah Arda
0000-0002-5496-3764
Türkiye

Mehmet Demir
0009-0007-6105-3439
Türkiye

Samet Çelebi ^*
0000-0002-4616-3935
Türkiye

Üsame Demir
0000-0001-7383-1428
Türkiye

Ömer Seçgin
0000-0001-6158-3164
Türkiye

Publication Date

April 1, 2026

Submission Date

February 23, 2026

Acceptance Date

March 27, 2026

Published in Issue

Year 2026 Volume: 10 Number: 1

DOI

https://doi.org/10.30939/ijastech..1896122

IZ

https://izlik.org/JA34CF28BL

Cite

RIS / Bibtex

APA

Arda, E., Demir, M., Çelebi, S., Demir, Ü., & Seçgin, Ö. (2026). Leveraging Advanced Machine Learning Algorithms for Energy Efficiency and Carbon Footprint Reduction in Diesel Engines. International Journal of Automotive Science And Technology, 10(1), 241-259. https://doi.org/10.30939/ijastech..1896122

AMA

1.Arda E, Demir M, Çelebi S, Demir Ü, Seçgin Ö. Leveraging Advanced Machine Learning Algorithms for Energy Efficiency and Carbon Footprint Reduction in Diesel Engines. IJASTECH. 2026;10(1):241-259. doi:10.30939/ijastech.1896122

Chicago

Arda, Emrah, Mehmet Demir, Samet Çelebi, Üsame Demir, and Ömer Seçgin. 2026. “Leveraging Advanced Machine Learning Algorithms for Energy Efficiency and Carbon Footprint Reduction in Diesel Engines”. International Journal of Automotive Science And Technology 10 (1): 241-59. https://doi.org/10.30939/ijastech. 1896122.

EndNote

Arda E, Demir M, Çelebi S, Demir Ü, Seçgin Ö (April 1, 2026) Leveraging Advanced Machine Learning Algorithms for Energy Efficiency and Carbon Footprint Reduction in Diesel Engines. International Journal of Automotive Science And Technology 10 1 241–259.

IEEE

[1]E. Arda, M. Demir, S. Çelebi, Ü. Demir, and Ö. Seçgin, “Leveraging Advanced Machine Learning Algorithms for Energy Efficiency and Carbon Footprint Reduction in Diesel Engines”, IJASTECH, vol. 10, no. 1, pp. 241–259, Apr. 2026, doi: 10.30939/ijastech..1896122.

ISNAD

Arda, Emrah - Demir, Mehmet - Çelebi, Samet - Demir, Üsame - Seçgin, Ömer. “Leveraging Advanced Machine Learning Algorithms for Energy Efficiency and Carbon Footprint Reduction in Diesel Engines”. International Journal of Automotive Science And Technology 10/1 (April 1, 2026): 241-259. https://doi.org/10.30939/ijastech. 1896122.

JAMA

1.Arda E, Demir M, Çelebi S, Demir Ü, Seçgin Ö. Leveraging Advanced Machine Learning Algorithms for Energy Efficiency and Carbon Footprint Reduction in Diesel Engines. IJASTECH. 2026;10:241–259.

MLA

Arda, Emrah, et al. “Leveraging Advanced Machine Learning Algorithms for Energy Efficiency and Carbon Footprint Reduction in Diesel Engines”. International Journal of Automotive Science And Technology, vol. 10, no. 1, Apr. 2026, pp. 241-59, doi:10.30939/ijastech. 1896122.

Vancouver

1.Emrah Arda, Mehmet Demir, Samet Çelebi, Üsame Demir, Ömer Seçgin. Leveraging Advanced Machine Learning Algorithms for Energy Efficiency and Carbon Footprint Reduction in Diesel Engines. IJASTECH. 2026 Apr. 1;10(1):241-59. doi:10.30939/ijastech. 1896122