Test verification and design of the bicycle frame parameters

Abstract

Research on design of bicycles is concentrated on mechanism and auto appearance design, however few on matches between the bike and the rider. Since unreasonable human-bike relationship leads to both riders’ worn-out joints and muscle injuries, the design of bicycles should focus on the matching. In order to find the best position of human-bike system, simulation experiments on riding comfort under different riding postures are done with the lifemode software employed to facilitate the cycling process as well as to obtain the best position and the size function of it. With BP neural network and GA, analyzing simulation data, conducting regression analysis of parameters on different heights and bike frames, the equation of best position of human-bike system is gained at last. In addition, after selecting testers, customized bikes based on testers’ height dimensions are produced according to the size function. By analyzing and comparing the experimental data that are collected from testers when riding common bicycles and customized bicycles, it is concluded that customized bicycles are four times even six times as comfortable as common ones. The equation of best position of human-bike system is applied to improve bikes’ function, and the new direction on future design of bicycle frame parameters is presented.