With real-time models of friction that take velocity as input, accuracy depends in great part on adequately estimating velocity from position measurements. This process can be sensitive to noise, especially at high sampling rates. In audio-haptic acoustic simulations, often characterized by friction-induced, relaxation-type stick-slip oscillations, this gives a gritty, dry haptic feel and a raspy, unnatural sound. Numerous techniques have been proposed, but each depend on tuning parameters so that they may offer a good trade-off between delay and noise rejection. In an effort to compare fairly, each of thirteen methods considered in the present study was automatically optimized and evaluated; finally a subset of these were compared subjectively. Results suggest that no one method is ideal for all gain levels, though the best general performance was found by using a sliding-mode differentiator as input to a Kalman integrator. An additional conclusion is that estimators do not approach the quality available in physical velocity transduction, and therefore such sensors should be considered in haptic device design.