Rapid fleet condition analysis through correlating basic vehicle tracking data with engine oil ft-ir spectra

Abstract

Engine oil condition and tribological performance are strongly interrelated. Accordingly, oil condition monitoring is common in various applications. This is especially important, as oil condition depends on the fueling and utilization profile of an internal combustion engine. Common practice involves the measurement of various parameters, such as the total acid number and total base number, oxidation, nitration, viscosity, and elemental composition; thus, it can be time-consuming and resource-intensive. This study provides a methodology for rapid analysis for large vehicle fleets or sample sizes, using only Fourier-transformed infrared spectroscopy and the subsequent multivariate data analysis offers a rapid alternative to commonly available methods. The described method provides a rapid, cost-efficient, and intuitive approach to uncovering differences in the oil condition. Furthermore, understanding the underlying reasons in engine construction and the resulting chemical degradation is also possible.