Coupled Optimization of Groove Texture for Parallel Ring–Ring Friction Pairs: Theory and Experiments

The geometric shape and area ratio of surface textures have a significant influence on the tribological performance. A numerical optimization method based on the genetic algorithm and sequential quadratic programming algorithm is used to optimize the geometric shape and area ratio of surface textures to achieve the highest load-carrying capacity (LCC) for parallel ring–ring friction pairs. The mass-conserving Jacobsson–Floberg–Olsson model is employed to precisely calculate the cavitation in the groove texture for LCC optimization. The results show that a more satisfactory global optimal solution of the groove textures can be obtained when the groove shape and the area ratio are considered simultaneously. The optimal groove texture, a chevron shape with a flat front and an area ratio of 40.4%, shows the lowest and stable friction coefficient under different experimental conditions.