Fenghui Shi

Optimization of a Semi-Active Shock Absorber Using a Genetic Algorithm

We propose an optimization method for a semi-active shock absorber for use in aircraft landing gear using Carroll’s FORTRAN Genetic Algorithm (GA) Driver. This method is compared with Powell’s conjugate direction method, a nonlinear programming (NP) approach, which uses not gradients, but only function values. In these optimizations, we handle variations in the maximum vertical acceleration of an aircraft during landing caused by the variation of the aircraft mass due to variations in the number of passengers and the amounts of cargo and fuel. The maximum vertical acceleration of an aircraft is set as an objective function to be minimized. Design variables searched in the first step of this optimization are discrete orifice areas formed by the outer surface of a hollow metering pin and a hole in the semi-active shock absorber. The design variable searched in the second step is an orifice area which is controlled based on the mass variation. For the GA runs, the ratio of the total number of optimum and near-optimum solutions to the total number of runs was greater than that for the NP runs. In addition, for the total GA runs, the total number of function evaluations per total number of optimum and near-optimum solutions was greater than that for the total NP runs. The optimum semi-active shock absorber is compared to the optimum passive shock absorber with respect to the variation of the acceleration of the aircraft mass. The ratio of maximum acceleration in the semi-active shock absorber to that in the passive shock absorber is 0.79 when the mass ratio is 0.65 maximum mass and is 0.58 when the mass ratio is 0.31 maximum mass.Copyright