Robust Piston Design and Optimization Using Piston Secondary Motion Analysis

To address the conflicting goals of minimal piston friction and minimal piston noise, a dynamic power cylinder model was developed to predict piston motion and side loads within the cylinder. This correlated model was the basis of a comprehensive analytical design of experiments (DOE) where both piston noise and piston friction were monitored. The results of the DOE were used to generate metamodels for piston friction and for piston noise. To insure design robustness, variability was introduced into the surrogate models via First Order Reliability Method (FORM). A Pareto curve using 99% probability was constructed and a piston robust to both noise and friction was selected.