This paper presents enhancements to a previously developed mixed-lubrication ring-pack model that has been used extensively in the automotive industry in predicting piston-ring/liner oil film thickness, friction and oil-transport processes along the liner. The previous model considers three lubrication regimes, shear thinning of the lubricant, and the unsteady wetting conditions of the rings at the leading and trailing edges. The model incorporates the effects of surface roughness by using Patir and Cheng’s average flow model and the Greenwood and Tripp statistical asperity contact model, assuming a Gaussian distribution of surface roughness. However, as a result of the methods used to machine a cylinder liner and the wear-in process observed in engines, the cylinder liner finish is highly non-Gaussian. The purpose of this current study is to understand the effects of additional surface parameters other than Gaussian root-mean-square surface roughness on piston ring-pack friction in the context of a natural gas reciprocating engine ring/liner interface. In general, the surface roughness of a cylinder liner is negatively skewed. Applying similar methodology published in the literature, a wide variety of non-Gaussian probability density functions were generated in terms of the skewness of the cylinder liner surface. These probability density functions were implemented into the Greenwood and Tripp asperity contact model, and subsequently into the traditional MIT ring-pack friction model. The effects of surface skewness on flow were approximated using Gaussian flow factors and a simple truncation method. The enhanced model was studied in conjunction with results from an existing ring-pack dynamic model that provided the dynamic twists of the rings relative to the liner and inter-ring pressures. In this manner, a detailed analysis of the effects of engineered cylinder liner finish on reducing friction losses was performed.
A State-Space Calculus for Rational Probability Density Functions and Applications to Non-Gaussian Filtering
