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Reduction of the visibility of a motor generator set in urban conditions using artificial intelligence technologies

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Category: Content №4 2026

Last Updated on 24 August 2026

Published on 30 November -0001

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Authors:

V. V. Krivda, orcid.org/0000-0002-8304-2016, Dnipro University of Technology, Dnipro, Ukraine

I. M. Nikitchenko, orcid.org/0000-0002-9481-4296, Kharkiv National Automobile and Highway University, Kharkiv, Ukraine

O. I. Voronkov, orcid.org/0000-0003-2744-7948, Kharkiv National Automobile and Highway University, Kharkiv, Ukraine

A. M. Avramenko*, orcid.org/0000-0001-8130-1881, Kharkiv National Automobile and Highway University, Kharkiv, Ukraine; A. M. Pidhornyi Institute of Power Machines and Systems of the National Academy of Sciences of Ukraine, Kharkiv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

V. M. Manoylo, orcid.org/0000-0003-2208-4404, Kharkiv National Automobile and Highway University, Kharkiv, Ukraine

* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

повний текст / full article

Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2026, (4): 045 - 052

https://doi.org/10.33271/nvngu/2026-4/045

Abstract:

Purpose. To develop a method for reducing the visibility of a multi fuel container type motor generator set in urban conditions. The approach is based on lowering the exhaust gas (EG) temperature and optimising the operation of internal combustion engine (ICE) auxiliary systems using artificial intelligence technologies.

Methodology. The scientific research is based on methods of comparative numerical experimentation. Modern numerical techniques are used to simulate the operating processes of a multi fuel motor generator set running on diesel fuel and pipeline methane, as well as the flow of exhaust gases and fresh air in an ejector mixer and in the flow section of the exhaust system. In this study, the pilot dose of diesel fuel was considered within 10 % of the cycle delivery.

Findings. Changes in the technical and economic performance indicators of the motor generator set were evaluated depending on the type of fuel. Characteristics of thermal emissions with the exhaust gases were obtained, and approaches were proposed to reduce infrared emission visibility using various methods. To increase the efficiency of the ICE and reduce heat emissions into the environment, the study proposes applying artificial intelligence technologies to control heat and mass transfer processes in the ICE and its auxiliary systems. It was shown that, in the gas diesel mode at nominal power, EG temperature is 17 °C higher than in the pure diesel mode. The developed ejector mixing system made it possible to reduce EG temperature by 114 °C at nominal power in the gas diesel mode.

Originality. The research established the effect of diluting EG with fresh air on temperature reduction and developed scientific and practical recommendations for selecting ejector mixer parameters depending on the structural and operational parameters of the motor generator set and the type of fuel. It was shown that controlling ICE auxiliary systems through artificial intelligence technologies – depending on environmental conditions, fuel type and operating mode – optimises energy consumption for auxiliary systems. This reduces mechanical losses for auxiliary drives and, consequently, improves the operating performance of the multi fuel motor generator set.

Practical value. Lowering EG temperature to reduce the visibility of a multi fuel motor generator set in the infrared spectrum complicates its detection by modern unmanned surveillance and information gathering systems.

Keywords: artificial intelligence, motor generator set, infrared spectrum, heat and mass transfer

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