<p>This study systematically investigates the influence of surface roughness on the wear behavior of TC11 titanium alloy through a combined approach of friction and wear experiments and finite element simulation. Two fractal surface modeling methods, namely the midpoint displacement method and the Weierstrass-Mandelbrot fractal function, were employed to construct rough surface models with different surface roughness values (0.2 μm, 0.4 μm, 0.8 μm). Wear simulation analysis was subsequently conducted using an energy wear model. Experimental results indicate that as surface roughness increases, the friction coefficient rises, the time to reach a stable wear stage is delayed, and both wear depth and wear rate increase significantly. Scanning electron microscopy morphology analysis reveals that increased surface roughness leads to the deepening of ploughing grooves, enlargement of wear debris size, and a higher proportion of adhesive wear. Finite element simulation results demonstrate that the fractal surface generated by the Weierstrass-Mandelbrot function more closely approximates the actual surface topography and exhibits smaller wear prediction errors. This validates the effectiveness and reliability of combining fractal surface modeling with the energy wear model for wear prediction. This research elucidates the mechanism by which surface roughness influences wear, providing a theoretical basis for the anti-friction and wear-resistant design of TC11 titanium alloy.</p>