Speed profile optimisation for a semi-trailer truck based on a hybrid fuel consumption model with automatic calibration based on CAN bus data

DOI: https://doi.org/10.30686/1609-9192-2026-5-178-185

Читать на русском языке Artem S. Dubrovskii, Sergey S. Shadrin, Daria A. Makarova, Yury M. Furletov
Moscow Polytechnic University, Moscow, Russian Federation
Mining Industry Journal (Gornaya Promyshlennost) №5/ 2026 p. 178-185

Summary: The paper proposes a method for optimising the speed profile of a long-haul semi-trailer truck that combines a physical fuel consumption model with a machine-learning correction with automatic calibration using on-board CAN bus data. The physical component is built on the tractive balance equation, which parameters, i.e. the power transmission efficiency, rolling resistance coefficient, brake-specific fuel consumption and lumped mechanical losses, are identified without bench testing by minimising the difference between the computed and the measured instantaneous fuel rate using the Powell's method; calibration is verified against the cumulative fuel counter (SAE J1939). The correction is implemented with the LightGBM algorithm that approximates the rest of the physical model; for the first time the current gear signal extracted directly from the CAN bus is used as an additional feature. The optimal speed profile is obtained by dynamic programming subject to a constraint on the travel-time increase; the speed range is lumped into 13 values within 60–80 km/h. The method was verified using a field trial with a Mercedes-Benz Actros 1845 truck on the M-11 «Neva» motorway (Moscow – Saint Petersburg, 672.5 km; about 14 million CAN records processed in under two minutes). The calibration error was 3.6%; introduction of the gear feature reduced the prediction root-mean-square error from 13.7 to 11.5 L/100 km (by 16%) and the cumulative-consumption deviation down to 1.4%. The computed fuel saving reached 9.3% at the travel time increased by less than 0.6%. Numerical simulation using the Moscow – Kazan route (809.1 km) confirmed the scalability: a 10.4% saving at a 2.8% time increase without model re-calibration.

Keywords: semi-trailer truck, fuel consumption, CAN bus, SAE J1939, tractive balance, dynamic programming, LightGBM, hybrid model, speed optimisation, eco-driving

Acknowledgements: The project was carried out with the financial support of the Moscow Polytechnic University under the V.E. Fortov grant programme (4 th Round).

For citation: Dubrovskii Artem S., Shadrin Sergey S., Makarova Daria A., Furletov Yury M. Speed profile optimisation for a semi-trailer truck based on a hybrid fuel consumption model with automatic calibration based on CAN bus data. Mining Industry Journal (Gornaya Promyshlennost). 2026;(5):178–185. https://doi.org/10.30686/1609-9192-2026-5-178-185

Article info

Received: 06.06.2026

Revised: 15.07.2026

Accepted: 17.07.2026

Authors info

Dubrovskii Artem S. – Lecturer, Advanced Engineering School of Technological Leadership FDR, Moscow Polytechnic University, Moscow, Russian Federation; https://orcid.org/0009-0001-1685-7039; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Shadrin Sergey S. – Dr. Sci. (Eng.), Professor, Advanced Engineering School of Technological Leadership FDR, Moscow Polytechnic University, Moscow, Russian Federation; https://orcid.org/0000-0002-2606-9984; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Makarova Daria A. – Cand. Sci. (Eng.), Senior Lecturer, Advanced Engineering School of Technological Leadership FDR, Moscow Polytechnic University, Moscow, Russian Federation; https://orcid.org/0000-0002-0752-5075; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Furletov Yury M. – Cand. Sci. (Eng.), Associate Professor, Advanced Engineering School of Technological Leadership FDR, Moscow Polytechnic University, Moscow, Russian Federation; https://orcid.org/0000-0002-5180-4899; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

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