Optimizing E-Bike Controls for Human-bike Interaction to Enhance Riding Experience and Efficiency

Abstract

E-bikes are now used for sports, rehabilitation, and work, not just commuting. Riders adjust power assistance and transmission to handle different conditions and reach their desired physical load. This interaction between the rider, bike, and environment can become complex due to faster speeds, shorter response times, and varying conditions, potentially leading to discomfort. A study with 21 non-athletes explored how riders manage the physical load on e-bikes during a simulated indoor riding session with 66 stages of varying slope resistance. Participants controlled the e-bike to maintain a moderate intensity, and data on latency of e-bike control, number of controls, acceptable pedaling power, heart rate, and perceived exertion were collected. On average, riders made their control adjustment 5.3 seconds after a slope change and used 2.7 control attempts to reach an acceptable pedaling power. The study found that the most acceptable pedaling power were similar across different slopes, suggesting a consistent preferred load. Participants aimed to maintain stable pedaling power despite external disturbances, targeting a moderate exercise intensity (66.9% maximal heart rate and a rate of perceived exertion of 12.1). The findings indicate that it's possible to estimate a personal preferred load, which could inform future studies on maintaining this load and improving the e-bike riding experience.