Analysis of Dimensions of Surface Textures on Lubrication and Friction of an Engine 03-15-01-0001
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SAE International Journal of Engines-V131-3EJ
To improve the lubrication and friction of the crankpin bearing (CB) in the engine, the design of surface textures on the bearing surface is proposed and researched based on the CB hydrodynamic dynamic model. To enhance the reliability of the research results and its closeness to reality, the optimal CB parameters, the experimental data of the external dynamic load W0 acting on the crankpin, and the CB surface roughness in the well-known existing researches are referred to as input data for the simulation process. The effect of the distribution density {n, m}, diameter D, and depth of the microcircular textures hd on improving the lubrication and friction are then analyzed based on the indexes of the increase in the oil film pressure, decrease in the solid asperity contacts in the mixed lubrication region (MLR), friction force, and coefficient of friction (COF) between the crankpin and bearing surfaces, respectively. The results indicate that the application of surface textures on the bearing surface greatly ameliorates the lubrication and friction of the engine (LFE) compared to the optimal CB dimensions without textures. Particularly, the maximum pressure of the oil film with n = 12 is higher than that of n = 6, n = 18, and n = 0 by 5.6%, 2.5%, and 13.6%, respectively, and the surface textures with n = 12, m = 6, D < 1.0 mm, and hd = 15 μm have an obvious effect in enhancing the LFE. Therefore, the study and application of surface textures on the CB surface not only enhance the durability and fuel economy and reduce the friction power loss of the engine but also are the basis for application to other journal bearings to improve lubrication and friction performance.
Citation: Hua, W., Nguyen, V., and Le, V., "Analysis of Dimensions of Surface Textures on Lubrication and Friction of an Engine," SAE Int. J. Engines 15(1):3-13, 2022, https://doi.org/10.4271/03-15-01-0001. Download Citation
Author(s):
Wenlin Hua, Vanliem Nguyen, Vanquynh Le