Wear simulation analysis and prediction of cast aluminum alloy material based on ring and block geometric model

Abstract

Abstract Cast aluminium alloy pistons are widely used in engines, and their wear significantly affects their service life. The finite element simulation analysis approach can accurately predict the amount of wear, reducing product development and production time. This study investigated the wear resistance by incorporating alumina reinforcing particles into the cast aluminium alloy matrix. The friction coefficient was measured using the MM-200 friction and wear testing equipment, and the wear rate was estimated after introducing alumina particles with varying contents into the aluminium alloy matrix. It was found that the cast aluminium alloy with a particle concentration of 2 wt% exhibited the lowest wear rate. A realistic finite element model of ring block friction and wear was developed based on Archard's theory, and wear simulations were conducted for cast aluminium alloys with different particle concentrations. By comparing the experimental and simulated wear scar widths, it was observed that the simulation findings closely matched the experimental data, demonstrating the accuracy of the finite element model. Additionally, the long-term wear behavior of various particle reinforced cast aluminium alloys was predicted by extending the wear simulation duration, revealing the wear characteristics of these alloys with different particle concentrations.