Optimization of design and fatigue simulations for an electric assisted bicycle frame using uniform design and grey relational analysis

Abstract

The electric assisted bicycle is the new transportation tool in the 21st century. The proposal of this article is to upgrade the fatigue safety factor for an electric assisted bicycle frame by integrating the uniform design, Kriging interpolation, entropy weighting method, grey relational analysis, and genetic algorithm. According to EN 15194 standard, the main objective function, the fatigue safety factor for an electric assisted bicycle frame is examined by ANSYS/Workbench software under three fatigue testing simulations. Five geometry parameters of an electric assisted bicycle frame are nominated to be the improved control factors. Since all control factors are continuous in the design space, the uniform design is certainly developed to construct a series of simulation experiments. For each model in the uniform design table, the fatigue finite element analysis is utilized to calculate the fatigue safety factor. Applying the multi-objective optimization procedure, the optimal design version of an electric bicycle frame has been obtained. For the fatigue safety factor, the revised design model has a maximum improvement of 19.59% when compared to the original design. Summery, the fatigue safety factor has been effectively elevated by executing the innovative multi-objective optimization procedure for an electric assisted bicycle frame system.