| Title |
Improving diesel engine reliability using an optimal prognostic model to predict diesel engine emissions and performance using pure diesel and hydrogenated vegetable oil / |
| Authors |
Žvirblis, Tadas ; Hunicz, Jacek ; Matijošius, Jonas ; Rimkus, Alfredas ; Kilikevičius, Artūras ; Gęca, Michał |
| DOI |
10.17531/ein/174358 |
| Full Text |
|
| Is Part of |
Eksploatacja i niezawodność – Maintenance and reliability.. Warsaw : Polish Maintenance Society. 2023, vol. 25, iss. 4, p. 1-19.. ISSN 1507-2711. eISSN 2956-3860 |
| Keywords [eng] |
ANCOVA ; hydrotreated vegetable oil ; MAPE ; Statistical regression analysis ; linear regression models ; Engine’s reliability |
| Abstract [eng] |
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. |
| Published |
Warsaw : Polish Maintenance Society |
| Type |
Journal article |
| Language |
English |
| Publication date |
2023 |
| CC license |
|
