FTIR Spectrometry with PLS Regression for Rapid TBN Determination of Worn Mineral Engine Oils

Marie Sejkorová, Branislav Šarkan, Petr Veselík and Ivana Hurtová
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Marie Sejkorová: Department of Transport Means and Diagnostics, Faculty of Transport Engineering, University of Pardubice, 532 10 Pardubice, Czech Republic
Branislav Šarkan: Department of Road and Urban Transport, Faculty of Operation and Economics of Transport and Communications, University of Žilina, 010 26 Žilina, Slovakia
Petr Veselík: Department of Risk Engineering, Institute of Forensic Engineering, Brno University of Technology, 612 00 Brno, Czech Republic
Ivana Hurtová: Department of Transport Means and Diagnostics, Faculty of Transport Engineering, University of Pardubice, 532 10 Pardubice, Czech Republic

Energies, 2020, vol. 13, issue 23, 1-12

Abstract: The TBN (Total Base Number) parameter is generally recognized by both engine oil processors and engine manufacturers as a key factor of oil quality. This is especially true for lubricating oils used in diesel and gas engines, which are exposed to relatively high temperatures and, therefore, require more effective protection against degradation. The FTIR spectrometry method together with a multivariate statistical software helped to create a model for the determination of TBN of worn motor oil SAE 15W-40 ACEA: E5/E7, API: CI-4. The best results were provided using a model FTIR with Partial Least Squares (PLS) regression in an overall range of 4000–650 cm −1 without the use of mathematical adjustments of the scanned spectra by derivation. Individual spectral information was condensed into nine principal components with linear combinations of the original absorbances at given wavenumbers that are mutually not correlated. A correlation coefficient (R) between values of TBN predicted by the FTIR-PLS model and values determined using a potentiometric titration in line with the ?SN ISO 3771 standard reached a value of 0.93. The Root Mean Square Error of Calibration (RMSEC) was determined to be 0.171 mg KOH.g −1 , and the Root Mean Square Error of Prediction (RMSEP) was determined to be 0.140 mg KOH.g −1 . The main advantage of the proposed FTIR-PLS model can be seen in a rapid determination and elimination of the necessity to work with dangerous chemicals. FTIR-PLS is used mainly in areas of oil analysis where the speed of analysis is often more important than high accuracy.

Keywords: oil analysis; engine oil; lubricants; FTIR spectrometry; total base number (TBN); partial least squares (PLS) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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