Abstract
In this work the problem of finding the optimum design of suspension system for two of the most commonly used Indian commercial three-wheeled motor vehicles namely Bajaj rear engine (RE) and Vikram front engine (FE) vehicle is formulated as an nonlinear optimization problem having decision variables as spring stiffness, viscous damping force of the front and rear suspension, wheelbase and track width. A real coded genetic algorithm (RCGA) has been applied to optimize system parameters to minimize the root mean square acceleration spectral density. The results are compared with Random search technique (RST2). It is observed that the solutions obtained using both algorithms lie within the International Standard Organization (ISO) 2631 values (ISO I [1997]). In all the models RCGA performs significantly better than RST.
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