Real‐time cycling cadence estimation via wheel speed measurement

Summary 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.