Lubrication efficiency of crankpin bearing using square-cylindrical textures of partial textures optimized by genetic algorithm

Abstract

Purpose This paper aims to propose an optimal design of the partial textures in the mixed lubrication regime of the crankpin bearing (CB) to maximize the CB's lubrication efficiency. Design/methodology/approach Based on a hybrid model between the slider-crank-mechanism dynamic and CB lubrication, the square-cylindrical textures (SCT) of partial textures designed on the CB’s mixed lubrication regime are researched. The effect of the density distributions of partial textures on CB’s lubrication efficiency is then evaluated via two indices of increasing the oil film pressure (p) and decreasing the frictional force (Ff) of the CB. The SCT’s geometrical dimensions are then optimized by the genetic algorithm to further improve the CB’s lubrication efficiency. Findings The results show that the SCT of partial textures optimized by the genetic algorithm has an obvious effect on enhancing CB’s lubrication efficiency. Especially, with the CB using the optimal SCT of partial textures (4 × 6), the maximum p is significantly increased by 3.7% and 8.2%, concurrently, the maximum Ff is evidently reduced by 9.5% and 21.6% in comparison with the SCT of partial textures (4 × 6) without optimization and the SCT of full textures (12 × 6) designed throughout the CB’s bearing surface, respectively. Originality/value The application of the optimal SCT of partial textures on the bearing surface not only is simple for the design-manufacturing process and maximizes CB’s lubrication efficiency but also can reduce the machining time, save cost and ensure the durability of the bearing compared to use the full textures designed throughout the CB’s bearing surface.