Real-time cycling cadence estimation via wheel speed measurement

The need to reduce emissions and improve mobility in overcrowded cities is promoting the use of bicycles as transportation means. Bicycles have a small footprint, are easy to use, and cost effective. The introduction of modern electric bicycles has also widened the user base, extending the reach of bicycles as a commuter's option. Electric bicycles, in order to meet regulation standards, need sensors that are not usually available on muscular bicycles, like torque or cadence sensors. In this paper, we develop a cadence estimation strategy based on the wheel speed encoder only, thus allowing to remove the cadence sensor. Specifically, we propose 2 approaches, ie, a direct cadence estimate and an indirect one via gear ratio estimate. Both estimation problems are shown to be equivalent to a frequency tracking problem, which can be solved by Kalman filtering. The final algorithm embeds a logic supervisor that guarantees the reliability of the procedure in all working conditions, including freewheeling. The whole analysis and development are based upon a thorough experimental campaign using an instrumented bicycle.