Multi-objective optimization framework of a vehicle door design in the slamming event for optimal dynamic performances

The slamming acoustic of a vehicle door is objectively not associated to the inherent character of the automobile, however, it is associated to the inherent structure of the vehicle door, which is a vital subjective performance to evaluate the vehicle. Although it has been recognized that static indicators may engender an inferior design result in engineering practice, the majority studies in the literature have not considered dynamic indicators for the door slamming event. This paper presents a multi-objective optimization (MOO) framework of a vehicle door design in the slamming event for optimal dynamic performances. In our previous study we have obtained the transient excitation forces through the transfer path analysis (TPA), lab experiment and bench test. These transient excitation forces will be the input for the MOO algorithm. The dimensions of the vehicle door structure main components are considered as design variables. The objective functions include the first natural frequency obtained by semi constrained modal analysis, the mass of the vehicle door, and the maximum amplitude of the target points on the vehicle door's glass. The constraint functions include the design variable bounds, dynamic stiffness constraints of the four mounting points for the glass run channel system. In order to promote the efficiency of subsequent optimization, the response surface method (RSM) is employed instead of timeconsuming finite element method. The multi-objective particle swarm optimization (MOPSO) algorithm is implemented to conduct the dynamic indicators optimization. The results show that the proposed optimization framework is successful of achieving a reliable solution with a uniformly distributed Pareto boundary, and it is recommended to choose an optimal result from relatively insensitive regions that meet the requirements. It is shown that the simulation response of the optimized door structure can reduce the acoustic pressure amplitude at the driver's right ear employed BEA technique. The proposed framework can be adapted to optimize door structural design for any vehicle door to improve noise, vibration, and harshness (NVH) performance. (c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

The study introduces a multi-objective optimization framework for optimizing the dynamic performance of vehicle door design, by taking into account the dimensions of the main components of the door structure as design variables. Results show that the optimized framework can effectively reduce the acoustic pressure amplitude at the driver's right ear.