关键词: 汽车尾门, 模态分析, 响应面模型, 多目标遗传算法

Abstract: Resonance significantly amplifies the vibration and noise of the tailgate,seriously affecting ride comfort,accelerating structural fatigue and component damage,and reducing the safety and reliability of the vehicle. To address the resonance issue of a certain SUV tailgate,firstly,a finite element model of the tailgate was established and modal analysis was conducted to locate the sensitive orders that were prone to resonance. Then,through sensitivity analysis, the sheet metal parts that significantly affect the seventh modal frequency of the tailgate were identified,and the thickness of the sheet metal parts was used as the design variable. Using Hammersley sampling method for Design Of Experiments (DOE), based on DOE sampling data,a response surface model for mass and seventh order modal frequency was fitted using least squares regression and radial basis function. Finally,with the optimization objective of maximizing the seventh modal frequency of the tailgate and minimizing the total mass of the tailgate,a Multi-Objective Genetic Algorithm was used for optimization. The results showed that after optimization,the first-order torsional frequency of the tailgate increased from 33.8 Hz to 36.2 Hz,avoiding resonance frequency with the white body. The total mass of the tailgate decreased by 5.4 %. The optimized design variable parameters were verified in three typical operating conditions in the tailgate finite element model,and the results showed that the optimization objectives met the design requirements.

Key words: car tailgate, modal analysis, response surface model, Multi-Objective Genetic Algorithm (MOGA)