Search Results

A new math-based piston noise model is proposed. It is based on a EHD (elastohydrodynamic) piston lubrication and secondary dynamic analysis. The model predicts the force on the bore wall as a function of time, which is then transformed to the frequency domain. The dynamic calculations of the model were validated against a closed form solution for a simple 1-D model. The model was applied to a production V8 engine. Predictions of the model compared well with block acceleration measurements for the same engine both in relative magnitude and frequencies. Effects of changing clearance and oil supply were also investigated using the model.

A comprehensive computer package, FLARE, has been developed for carrying out Friction and Lubrication Analysis of Reciprocating Engines. FLARE considers four major lubricated components in an automotive engine -- piston skirt, piston rings, bearings, and valve train. Hydrodynamic, mixed, and boundary lubrication models are used, as appropriate, to model the lubrication phenomena. All the analytical models are based on solution of governing equations. Three levels of analyses with varying degrees of detail have been developed. Availability of different levels provides the flexibility of matching the complexity and accuracy of the analysis with the objective of the analysis. An empirical engine friction model, which is based on experimental data, is also available. Many user-friendly features are built into the FLARE system to make it easier to use for design engineers. This paper gives a brief overview of all the analysis sub-models incorporated into FLARE.

Comparisons are made between friction predictions of the FLARE (Friction and Lubrication Analysis of Reciprocating Engines) computer code and experimental data for the purpose of validating FLARE. An in-line four-cylinder engine under motoring conditions was selected for doing the experiments. Three major friction producing subassemblies were considered: piston assembly, crankshaft main bearings, and valve train. A Taguchi-type L16 matrix was used for the piston assembly, while an L8 matrix was used for the valve train. A traditional approach (varying one parameter at a time) was used for crankshaft main bearings. The agreement between experimental measurements and FLARE predictions, for all the cases studied, is very good. The match is closest for the valve train, followed by the crankshaft main bearings and piston assembly. In addition, trends and effects of changing design parameters are predicted correctly by FLARE.