This paper deals with the friction performance results for various new concept piston skirt profiles. The program was conducted under the assumption that friction performance varies by the total amount of oil available at each crank angle in each stroke and the instantaneous distribution of the oil film over the piston skirt area.In previous papers [1,2] it was that lower friction designs would be expected to show higher skirt slap noise. This paper discusses the correlation between friction and skirt slap for each new concept profile design.Finally, this paper explains the friction reduction mechanism for the test samples for each stroke of the engine cycle by observing the skirt movement and oil lubrication pattern using a visualization engine.
Piston design is a challenging engineering problem which involves complex physics and requires satisfying multiple performance objectives. Uncertainty in piston operating conditions and variability in piston design variables are inevitable and must be accounted for. The piston assembly can be a major source of engine mechanical friction and cold start noise, if not designed properly. In this paper, an analytical piston model is used in a deterministic and probabilistic (reliability-based) multi-objective design optimization process to obtain an optimal piston design. The model predicts piston performance in terms of scuffing, friction and noise, In order to keep the computational cost low, efficient and accurate metamodels of the piston performance metrics are used. The Pareto set of all optimal solutions is calculated allowing the designer to choose the "best" solution according to trade-offs among the multiple objectives. Our multi-objective optimization method is demonstrated with simple examples and applied in the design of an automotive piston.
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