The multi-objective optimization of the damaged aircraft trailer based on a dynamic model

Abstract

A damaged aircraft trailer is an essential piece of airport emergency rescue equipment which is made up of frames and multiple suspensions. As a load–force transferring mechanism, the suspension bears heavy loads which can cause fatigue damage. Therefore, reducing the maximum stress of the suspension is necessary to improve the vehicle performance. Besides, lightweight design should be considered to reduce energy consumption. Thus, lighter suspension which can bear more pressure is the optimization objective of this research. A multi-objective optimization method was carried out to analyze the suspension arm of a damaged aircraft trailer. Firstly, to investigate the dynamic characteristics and the reliability of the damaged aircraft trailer, a detailed three combined damaged aircraft trailers model was built. Based on the flexible-rigid coupled method, dynamic simulation of the damaged aircraft trailer was conducted in MSC.ADAMS. Then a suspension model was established, and the stress under different loads was measured to verify the accuracy of the finite element suspension arm model by experiments. Based on the design of experiment method, the effect of suspension arm parameters were obtained to build the approximate models. Besides, the influences of some effect parameters on optimal objectives were analyzed based on the surface response method. During the optimization process, a non-dominated sorting genetic algorithm II was adopted to optimize the mass and stress of the suspension arm. The results show that the mass of the suspension arm is reduced from 146.81 kg to 126.69 kg, which is a reduction of 14%. The maximum von Mises stress is changed from 325 MPa to 297 MPa, which is a decrease of 8.6%. This optimal method can be extended to the overall vehicle, which has an important significance in the whole damaged aircraft trailer characteristics improvement design.

Keywords

Damaged aircraft trailer dynamic model design of experiment method multi-objective optimization response surface model

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