Multi-objective optimization is always a difficult and hot problem for the static and dynamic performance and lightweight optimization design of a body-in-white (BIW). In this regard, a hybrid method coupled with NSGA-III and entropy weighted TOPSIS methods was put forward here. Effects of each design variable on the BIW performance was studied by means of the contribution method so as to optimize various design variables. Further, an experimental design was carried out by means of a radial basis function model to approximate each performance index of the automotive body. On the base of that, a comprehensive method where the Pareto frontier is searched by means of NSGA-III while the optimal solution is selected by means of the entropy weighted TOPSIS method was proposed based on lightweight, static and dynamic performances to analyze BIW performances to determine the contradictory optimal solution among various BIW factors. Afterward, our numerical verifications demonstrate that the BIW performances are improved significantly so that it can be feasible to optimize static and dynamic BIW performances and the lightweight performance of the BIW can be guaranteed accordingly.

Sensitivity analysis and response surface methods were employed to optimize the structural modal of SUV doors. A finite element numerical simulation model was established and was calibrated by restraint modal tests. To screen out highly sensitive panels, a sensitivity analysis for the thickness of door panels was proposed based on the fifth-order modal frequency of the door. Data points were obtained by a faced central composite design with the design variables from the thickness of the highly sensitive panels, and a second-order explicit response surface function of the fifth-order modal frequency of the vehicle door was established. An optimization model was established according to the response surface method. The final results demonstrate that the modal-frequency matching of the door and body in white was optimized after changing the thicknesses, with a 5.74% material reduction.

Tail-welded blanks (TWBs) are widely used in automotive bodies to improve the structural performance and reduce weight. The stiffness and modal lightweight design optimisation of TWBs for automotive doors was performed in this study. The finite element model was validated through physical experiments. An L27 (3¹²) Taguchi orthogonal array was used to collect the sample points. The multi-objective optimisation problem was transformed into a single-objective optimisation problem based on the grey relational degree. The optimal combination of structural design parameters was obtained for a tail-welded door using the proposed method, and the weight of the door structure was reduced by 2.83 kg. The proposed optimisation method has fewer iterations and a lower computational cost, enabling the design of lightweight TWBs.

Accurate prediction of the dynamic stiffness of rubber bushings is crucial for optimizing vehicle vibration and noise performance. However, this task is highly challenging due to various influencing factors such as frequency and amplitude. Consequently, there has been limited research conducted in this area thus far. This paper presents a novel approach for predicting the dynamic stiffness of rubber bushings. The frequency and amplitude dependencies of rubber bushings were thoroughly investigated through dynamic loading tests. A comprehensive model for rubber bushings, incorporating parallel connections of elastic elements, friction elements, and higher-order fractional derivative viscous elements, was established. The model parameters were accurately identified using the GA-BP method. The results demonstrate that the proposed model exhibits a high level of precision in estimating dynamic stiffness across a frequency range of 0–200 Hz. In comparison to the conventional model, the proposed approach enables more precise computation of interior sound pressure response and enhances vehicle simulation accuracy.