Optimizing the Parameters of the Partial Textures of the Crankpin Bearing to Enhance the Lubrication Performance of an Engine

To enhance the lubrication performance of the crankpin bearing (CB) at the elastic hydrodynamic lubrication regime (EHLR), the spherical dimples (SD) of the partial textures (PT) is designed on the EHLR of the CB. Based on a hydrodynamic model of the slider-crank mechanism (SCM) combined with the CB lubrication and a multi-objective optimization program of the genetic algorithm (MOGA), the initial design parameters of PT including the depth h_sij and the diameter D_ij of each SD defined as chromosomes in the MOGA are then optimized to further enhance the CB’s lubrication performance. Three indexes of the oil film pressure p, friction force F _f, and friction coefficient μ of the CB are chosen as the objective functions. The research results indicate that based on the optimal approach of the MOGA with its good stability and repeatability, the CB’s lubrication performance is remarkably improved by the optimal parameters in comparison with the initial parameters of the SD. Particularly, at the EHLR of the CB, both the maximum values of the p and F _f are significantly reduced by 7.7% and 14.6% compared to the initial parameters of the PT; and by 8.6% and 19.9% in comparison with the initial parameters of the full textures (FT) designed on the bearing surface. Thus the application of the MOGA to optimize the SD design parameters can better improve the lubrication performance and durability of the CB of an engine.