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Development and Testing of an Innovative Oil Condition Sensor
- Amiyo Basu - Ford Motor Company ,
- Will Ruona - Ford Motor Company ,
- Garry Zawacki - Ford Motor Company ,
- Arup Gangopadhyay - Ford Motor Company ,
- Dave Scholl - Ford Motor Company ,
- Jaco Visser - Ford Motor Company ,
- Heiko Dobrinski - Hella Fahrzeugkomponenten GmbH ,
- Marco Doebrich - Hella Fahrzeugkomponenten GmbH
ISSN: 1946-3936, e-ISSN: 1946-3944
Published April 20, 2009 by SAE International in United States
Citation: Basu, A., Ruona, W., Zawacki, G., Gangopadhyay, A. et al., "Development and Testing of an Innovative Oil Condition Sensor," SAE Int. J. Engines 2(1):1327-1334, 2009, https://doi.org/10.4271/2009-01-1466.
In order to detect degradation of engine oil lubricant, bench testing along with a number of diesel-powered Ford trucks were instruments and tested. The purpose of the bench testing was primarily to determine performance aspects such as repeatability, hysteresis effects and so on. Vehicle testing was conducted by designing and installing a separate oil reservoir along with a circulation system which was mounted in the vicinity of the oil pan. An innovative oil sensor was directly installed on the reservoir which can measure five (5) independent oil parameters (viscosity, density, permittivity, conductance, temperature). In addition, the concept is capable of detecting the oil level continuously during normal engine operation. The sensing system consists of an ultrasonic transducer for the oil level detection as well as a Tuning Fork mechanical resonator for the oil condition measurement. Also, the sensor includes an intelligent Oil Condition Algorithm (OCA) which evaluates the incoming signals from the sensor and calculates the current oil quality considering additional information from the engine. The OCA can detect contaminants and extreme oil conditions at an early stage. The vehicles tests are conducted by utilizing a drive cycle that includes city as well as highway driving. The output generated by the sensor is processed via an on-board Data Acquisition Platform (DAP) on a real-time basis. The data collected was uploaded via telematics to a server for subsequent analysis. The results thus obtained and the performance of the sensor will be presented in this paper.