RESEARCH PAPER
Emissions, reliability and maintenance aspects of a dual-fuel engine (diesel-natural gas) using HVO additive and ANCOVA modeling
1
Mechanical Science Institute, Vilnius Gediminas Technical University, Lithuania
2
Department of Automobile Engineering, Vilnius Gediminas Technical University, Lithuania
3
Department of Transport Engineering, Vilniaus Kolegija Higher Education Institution, Lithuania
Submission date: 2025-04-16
Final revision date: 2025-06-03
Acceptance date: 2025-07-20
Online publication date: 2025-07-21
Publication date: 2025-07-21
Corresponding author
Jonas Matijošius
Mechanical Science Institute, Vilnius Gediminas Technical University, Plytines st. 25, 10105, Vilnius, Lithuania
Mechanical Science Institute, Vilnius Gediminas Technical University, Plytines st. 25, 10105, Vilnius, Lithuania
Eksploatacja i Niezawodność – Maintenance and Reliability 2026;28(1):208439
HIGHLIGHTS
- Increased NG ratio significantly reduces NOx and smoke emissions.
- HVO pilot fuel shortens ignition delay and lowers injector fouling.
- Dual fuel mode lessens engine thermal load and extends maintenance intervals.
- ANCOVA model predicts major engine parameters with MAPE as low as ~2%.
- Extended intervals and lower component stress improve engine reliability over time.
KEYWORDS
TOPICS
ABSTRACT
This paper presents an experimental and statistical study of a four-cylinder turbocharged compression ignition engine operating in dual-fuel mode with natural gas and liquid pilot fuel (diesel or hydrotreated vegetable oil). The main engine performance indicators, combustion process parameters and emissions were evaluated, as well as noise and vibration measurements were performed to determine the loading of structural elements. In order to highlight the factors affecting engine reliability and maintenance, the ANCOVA (analysis of covariance) methodology was applied, modeling the influence of load, natural gas fraction and sound pressure. The mean absolute percentage error shows that the model predicts the most important indicators quite accurately under various operating conditions. The developed ANCOVA model not only predicts engine characteristics under various load and fuel mixture conditions, but it also provides insights useful for engine maintenance planning and reliability assurance, especially in long-term or intensive operation.
ACKNOWLEDGEMENTS
This research was supported by the center of excellence project "Civil Engineering Research Center" (Grant No. S-A-UEI-23-5).
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| eISSN: | 2956-3860 |
| ISSN: | 1507-2711 |
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