Optimization of a passenger occupied seat with suspension system exposed to vertical vibrations using genetic algorithms

This paper presents a biomechanical model with seven degrees of freedom as a seated human exposed to vertical vibration. Experimental data is used to find the stiffness and damping parameters of the model. The data includes values of seat to head transmissibility, driving point mechanical impedance and apparent mass. The multi-objective function is used to obtain theoretical results similar to three different experimental cases. The unknown coefficients are calculated by a genetic algorithm. Improved results, in comparison with previous models, are achieved from the presented model. Next, this modified model is assembled on a quarter car and parameters of the cushion and the suspension system are simultaneously optimized. By using a genetic algorithm within a multi-objective function, the parameters of the quarter car model are determined, thereby yielding simultaneous optimization of the transmitted energy from road to passenger's head in the frequency domain and the acceleration of head and the crest factor coefficient in the time domain. Also, car stability is taken into account as a design constraint. The results indicate that by adjusting the parameters of the seat cushion and the suspension system, it is possible to bring about more ride comfort to the passenger.