In an era of accelerated engine efficiency development, the ability to accurately model lubricant performance is becoming increasingly important. The general behaviour of engine lubricant viscosity with temperature is well understood and for most applications the widely accepted models of Walther and Vogel are deemed accurate enough in their prediction of decreasing viscosity with increasing temperature. However, as we move further into a digitized age it becomes apparent there is a need for a single expression higher accuracy equation which captures this behaviour to better facilitate its use in automotive engineering simulation software (Computer Aided Engineering -CAE). Ideally it would be beneficial for a viscosity model to include standard viscosity parameters in a single expression that could be calibrated directly using standard viscosity measurements that are already in common use. A key aspect which underpins models of lubricated surfaces is the ability to accurately predict viscosity. Any errors in a viscosity prediction for the lubricant which might otherwise seem minor at atmospheric pressure are exacerbated by the near exponential response of viscosity to contact pressure. This reinforces the requirement for a simple accurate solution. In this paper a new single expression concept model has been explored refined and validated at both low and high shear rates and on both absolute and kinematic viscosity. Three key arrangements of the model are used as examples; a basic model (9), an enhanced model (10) and finally the enhanced model is examined over an extended temperature range (11). The benefits of each are explained, with the most advanced model accuracy investigated in greater depth and compared to measured data. The resultant error in the viscosity prediction is less than the quoted accuracy of the measuring equipment (0.2%) which then becomes the limiting accuracy factor for the model in this instance. Finally some examples of the model in use, embedded within CAE tools are discussed to demonstrate its applicability within more complex scenarios.
展开▼
