Using multiple linear regression to predict engine oil life
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F25%3A00142181" target="_blank" >RIV/00216224:14310/25:00142181 - isvavai.cz</a>
Result on the web
<a href="https://rdcu.be/eI2Ho" target="_blank" >https://rdcu.be/eI2Ho</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1038/s41598-025-18745-w" target="_blank" >10.1038/s41598-025-18745-w</a>
Alternative languages
Result language
angličtina
Original language name
Using multiple linear regression to predict engine oil life
Original language description
This paper deals with the use of multiple linear regression to predict the viscosity of engine oil at 100 °C based on the analysis of selected parameters obtained by Fourier transform infrared spectroscopy (FTIR). The spectral range (4000–650 cm−1), resolution (4 cm−1), and key pre-processing steps such as baseline correction, normalization, and noise filtering applied prior to modeling. A standardized laboratory method was used to analyze 221 samples of used motor oils. The prediction model was built based on the values of Total Base Number (TBN), fuel content, oxidation, sulphation and Anti-wear Particles (APP). Given the large number of potential predictors, stepwise regression was first used to select relevant variables, followed by Bayesian Model Averaging (BMA) to optimize model selection. Based on these methods, a regression relationship was developed for the prediction of viscosity at 100 °C. The calibration model was subsequently validated, and its accuracy was determined using the Root Mean Squared Error (RMSE) metric, it was 0.287. Finally, the obtained model was used to predict the lifetime of engine oil in diesel engines operating under severe conditions.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10102 - Applied mathematics
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Scientific Reports
ISSN
2045-2322
e-ISSN
2045-2322
Volume of the periodical
15
Issue of the periodical within the volume
33585
Country of publishing house
GB - UNITED KINGDOM
Number of pages
14
Pages from-to
33585
UT code for WoS article
001586154100003
EID of the result in the Scopus database
2-s2.0-105017650696