Optimal Design of Motorcycle Rear Suspension Systems Using Genetic Algorithms

Abstract

Acceleration, braking and turning capabilities are widely influenced by the parameters of the suspension systems. In this paper a geometric configuration of a rear suspension that fits a chosen target curve is obtained. The procedure followed in this study begins by choosing the topology of the rear suspension system. After that, the rear suspension characteristics are selected (highest and lowest force, progressiveness, squat ratio…). Subsequently, user-defined functions are used to obtain the position of each suspension element along the path and, later, to get the forces at each point of the system. Finally, a genetic algorithm is used to obtain an appropriate geometry of the rear suspension elements which fits the given requirements. An example is included to demonstrate the behavior and potential of the method. This strategy takes into account both the progressiveness and desired squat-ratio of the system, which have never been included in a rear suspension design before.