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Large motion mountain biking dynamics
Abstract:A bond graph model of a mountain bike and rider is created to develop baseline predictions for the performance of mountain bikes during large excursion maneuvers such as drops, jumps, crashes and rough terrain riding. The model assumes planar dynamics, a hard-tail (front suspension only) bicycle and a rider fixed to the bicycle. An algorithm is developed to allow tracking of a virtual tire-ground contact point for events that separate the wheels from the ground. This model would be most applicable to novice mountain bikers who maintain a nearly rigid relationship between their body and the bicycle as opposed to experienced riders who are versed in controlling the bicycle independent of the body. Simulations of a steep drop are performed for various initial conditions to qualitatively validate the predictions of the model. Results from this model are to be compared to experimental data and more complex models in later research, particularly models including a separate rider. The overarching goals of the research are to examine and understand the dynamics and control of interactions between a cyclist and mountain bike. Specific goals are to understand the improvement in performance afforded by an experienced rider, to hypothesize human control algorithms that allow riders to perform manoeuvres well and safely, to predict structural bike and body forces from these maneuvers and to quantify performance differences between hard-tail and full suspension bicycles.
Keywords:Mountain biking  Vehicle dynamics  Suspension systems  Bond graph modelling
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