Electrical Parameters as Diagnostics of Fresh Engine Oil Condition-Correlation with Test Voltage Frequency

• Published in: Sensors (Basel, Switzerland) Vol. 23; no. 8; p. 3981
• Main Authors: Wolak, Artur, Żywica, Ryszard, Molenda, Jarosław, Banach, Joanna Katarzyna
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 14.04.2023; MDPI
• Subjects: Automobile industry; Automobiles; Capacitance; Clustering; conductance; Diagnostic systems; Electric potential; Electric properties; Electrical conductivity; electrical parameters; Electrical resistivity; Frequency analysis; Frequency ranges; Impedance; impedance magnitude; Laboratories; Lubricants & lubrication; Lubricating oils; Parameters; phase shift angle; Q factors; Quality assessment; Sensors; Statistical analysis; Susceptance; Transportation equipment industry; Viscosity; Voltage; voltage frequency; Poland; United States > US; total base number; phase shift angle; capacitance; impedance magnitude; susceptance; engine oil; electrical parameters; conductance; voltage frequency; quality factor; total acid number
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s23083981

The aim of this study was to assess whether electrical parameters (capacitance and conductivity) of fresh engine oils-tested over a wide range of measurement voltage frequencies-can be used for oil quality assessment and its identification, based on physicochemical properties. The study encompassed 41 commercial engine oils with different quality ratings (American Petroleum Institute (API) and European Automobile Manufacturers' Association (ACEA)). As part of the study, the oils were tested for their total base number (TBN) and total acid number (TAN), as well as their electrical parameters, including impedance magnitude, phase shift angle, conductance, susceptance, capacitance and quality factor. Next, the results for all of the samples were examined for correlations between the mean electrical parameters and the test voltage frequency. A statistical analysis (k-means and agglomerative hierarchical clustering) was applied to group oils with similar readings, drawing on the values for all electrical parameters to produce group oils with the highest similarity to each other into clusters. The results show that the electrical-based diagnostics of fresh engine oils can serve as a highly selective method for identifying oil quality, offering much higher resolution than assessments based on the TBN or the TAN. This is further supported by the cluster analysis, with five clusters generated for electrical parameters of the oils, compared to only three generated for TAN- and TBN-based measurements. Out of all the tested electrical parameters, capacitance, impedance magnitude and quality factor were found to be the most promising for diagnostic purposes. The value of electrical parameters of fresh engine oils is mostly dependent on the test voltage frequency (with the exception of capacitance). The correlations identified in the course of the study can be used to select for those frequency ranges that offer the highest diagnostic utility.