Abstract

Standard and electric bicycles are expected to become the principal mean of transport for future short-range mobility. Solving the comfort problem is thus becoming more and more urgent, nonetheless it is known to be a hard task, especially because the cyclist is an active agent while pedaling. As far as we are aware, this is the first paper addressing the comfort problem during the gear shifting phase. Under non-restrictive assumptions, an algorithmic solution is developed providing an estimate for the best instant for comfort shifting. This problem is formulated as a local minimum acceleration point seeking. To solve it, the pedaling cadence is estimated from the rear wheel speed, after learning the gear ratios. Experiments performed on a real testing set-up are finally provided to assess the performance of the proposed approach.

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