TY - JOUR
T1 - Multi-objective optimization framework of a vehicle door design in the slamming event for optimal dynamic performances
AU - Liu, Zhe
AU - Gao, Yunkai
AU - Yang, James
AU - Xu, Xiang
AU - Fang, Jianguang
AU - Xie, Furong
N1 - Funding Information:
This work was supported by the National Key Research and Development Program of China (grant number 2016YFB0101602), the National Natural Science Foundation of China (grant number 51575399 ), and the Project of Shanghai Science and Technology Committee (grant number 20511104601). ZL, YG, and FX appreciate the financial support from these grants.
Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2022/2
Y1 - 2022/2
N2 - 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 time-consuming 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.
AB - 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 time-consuming 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.
KW - Automotive door
KW - Multi-objective optimization
KW - Vehicle door slamming event
KW - Vibro-acoustic analysis
UR - http://www.scopus.com/inward/record.url?scp=85119424817&partnerID=8YFLogxK
U2 - 10.1016/j.apacoust.2021.108526
DO - 10.1016/j.apacoust.2021.108526
M3 - Article
AN - SCOPUS:85119424817
VL - 187
JO - Applied Acoustics
JF - Applied Acoustics
SN - 0003-682X
M1 - 108526
ER -