An Effective Algorithm for Creating Precise Oil Level Information

Event
Commercial Vehicle Engineering Congress & Exhibition
Authors Abstract
Content
With the new developments in electronics, use of electronic sensors is becoming more common in today's vehicles. Oil level monitoring using electronic level sensor is one of them. In this paper, an algorithm developed for Ecotorq heavy duty diesel engines is presented and software measures developed to overcome typical application challenges are described.
The sensor used on the engine has a damping tube in which the oil flows through a very small hole to dampen the oil flow. The sensing method is ultrasonic sensing. Direct calculation of total amount of oil from oil level is not possible anytime, since a portion of the oil circulated in the engine varies with engine speed and some part of the oil trapped in the different regions of the engine changes with road conditions. Additionally, lubrication oil is not still while the engine and/or vehicle is running due to effect of crankshaft oil spill and vehicle movements. In order to evaluate the oil amount in the engine precise enough, the raw value from the sensor has to be corrected by an algorithm. The algorithm uses the previously calculated oil amount to utilize long-term averaging since the oil level change is expected to be small. It also has top-up detection and leakage detection functionalities to display sudden changes. For effective usage by the customer, the very last output of the algorithm is the volume of the oil that should be top-up. The algorithm was developed in MATLAB/Simulink environment by Ford Otosan and coded by Robert Bosch GmbH. The calibration methodology and results of functional tests performed by Ford Otosan are presented.
Meta TagsDetails
DOI
https://doi.org/10.4271/2008-01-2716
Pages
8
Citation
Hisar, G., and Ergen, O., "An Effective Algorithm for Creating Precise Oil Level Information," SAE Int. J. Commer. Veh. 1(1):508-515, 2009, https://doi.org/10.4271/2008-01-2716.
Additional Details
Publisher
Published
Oct 7, 2008
Product Code
2008-01-2716
Content Type
Journal Article
Language
English