Improving Diesel Engine Reliability Using an Optimal Prognostic Model to Predict Diesel Engine Emissions and Performance Using Pure Diesel and Hydrogenated Vegetable Oil

• Autorzy: Žvirblis Tadas , Hunicz Jacek , Matijošius Jonas , Rimkus Alfredas , Kilikevičius Artūras , Gęca Michał

Identyfikatory

DOI

10.17531/ein/174358

• Języki publikacji: EN

Abstrakty

EN

The reliability of internal combustion engines becomes an important aspect when traditional fuels with biofuels. Therefore, the development of prognostic models becomes very important for evaluating and predicting the replacement of traditional fuels with biofuels in internal combustion engines. The models have been made to model AVL 5402 engine emission, vibration, and sound pressure parameters using a three-stage statistical regression models. The fifteen parameters might be accurately predicted by a single statistic presented here. Both fuel type (diesel fuel and HVO) and engine parameters that can be adjusted were considered, since this analysis followed the symmetry of the methods. The data analysis process included three distinct steps and symmetric statistical regression testing was performed. The algorithm examined the effectiveness of various engine settings. Finally, the optimal fixed engine parameter and the optimal statistic were used to construct an ANCOVA model. The ANCOVA model improved the accuracy of prediction for all fifteen missing parameters.

Słowa kluczowe

EN

engine’s reliability; statistical regression analysis; linear regression models; ANCOVA; MAPE; hydrotreated vegetable oil

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2023
• Tom: Vol. 25, no. 4
• Strony: art. no. 174358
• Opis fizyczny: Bibliogr. 47 poz., rys., tab., wykr.

Twórcy

autor

Žvirblis Tadas

• Institute of Data Science and Digital Technologies, Vilnius University, Lithuania

• https://orcid.org/0000-0002-9368-8726

autor

Hunicz Jacek

• Faculty of Mechanical Engineering, Lublin University of Technology, Poland

• https://orcid.org/0000-0002-0188-6419

autor

Matijošius Jonas

• Institute of Mechanical science, Faculty of Mechanical Engineering, Vilnius Gediminas Technical University, Lithuania

• https://orcid.org/0000-0001-6006-9470

autor

Rimkus Alfredas

• Department of Automobile Engineering, Vilnius Gediminas Technical University, Lithuania

• https://orcid.org/0000-0001-8995-7180

autor

Kilikevičius Artūras

• Institute of Mechanical science, Faculty of Mechanical Engineering, Vilnius Gediminas Technical University, Lithuania

• https://orcid.org/0000-0002-4074-1773

autor

Gęca Michał

• Faculty of Mechanical Engineering, Lublin University of Technology, Poland

• https://orcid.org/0000-0002-2226-1645

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