Noise-vibration-harshness (NVH) design optimization problems have become major concerns in the vehicle product development process. The Body-in-White (BIW) plays an important role in determining the dynamic characteristics of vehicle system during the concept design phase. Finite Element (FE) models are commonly used for vehicle design. However, even though the speed of computers has been increased a lot, the simulation of FE models is still too time-consuming due to the increase in model complexity. For complex systems, like vehicle body structures, the numerous design variables and constraints make the FE simulations based optimization design inefficient. This calls for the development of a systematic and efficient approach that can effectively perform optimization to further improve the NVH performance, while satisfying the stringent design constraints.In the present work, an efficient method to optimize the structural dynamic response is proposed considering the low-frequency NVH performances. As a first step, to reduce computational burden, a response sensitivity analysis is performed to detect the most important variables prior to the design optimization. Then an analytical approximation model of vibration resonance peak is constructed and coupled with the adaptive simulated annealing (ASA) algorithm to replace the time-consuming finite element analysis. Subsequently, an optimization of NVH performance considering dynamic response is formulated and carried out. The methodology aims at improving the NVH behavior of body structure by simultaneously suppressing several resonance peaks. Finally, the proposed method and its process are successfully illustrated through a vehicle body example. The results demonstrate that the proposed method of incorporating response surface model with ASA algorithm is feasible and cost-efficient in solving the vibration optimization problem.

The traditional centralized control strategy to vibration suppression of large-scale thin plate structures may increase the design difficulty of the controller. In this article, a decentralized vibration active control method is proposed to suppress the vibration of the thin plate structure with smart constrained layer damping treatment. First, the dynamics model of the smart constrained layer damping plate is established based on the finite element method, and the characteristics of viscoelastic materials with temperature and frequency are described by Golla-Hughes-McTavish damping model. Subsequently, a decentralized subsystem control model is obtained from the balanced model reduction method and complex mode truncation method. The modal test proves that the theoretical model is accurate. Then, the particular emphasis is placed on the stability and vibration attenuation of a decentralized system, which is composed of multiple subsystems. The local state feedback stabilization, using interaction of local state feedback and output feedback, is introduced to achieve system stability. To solve the practical problem of local state feedback, a decentralized controller with an observer is developed by adopting the pole placement method. Finally, the numerical simulation and hardware-in-the-loop experiment under different excitation are performed to investigate the effectiveness of decentralized vibration active control. The results demonstrate that the decentralized controller can effectively suppress the vibration, especially under mixed periodic signal and Gauss white noise signal.

This paper presents a numerical modeling method combined with model updating techniques for the analysis of smart laminated structures with viscoelastic damping. Starting with finite element formulation, the dynamics model with piezoelectric actuators is derived based on the constitutive law of the multilayer plate structure. The frequency-dependent characteristics of the viscoelastic core are represented utilizing the anelastic displacement fields (ADF) parametric model in the time domain. The analytical model is validated experimentally and used to analyze the influencing factors of kinetic parameters under parametric variations. Emphasis is placed upon model updating for smart laminated structures to improve the accuracy of the numerical model. Key design variables are selected through the smoothing spline ANOVA statistical technique to mitigate the computational cost. This updating strategy not only corrects the natural frequencies but also improves the accuracy of damping prediction. The effectiveness of the approach is examined through an application problem of a smart laminated plate. It is shown that a good consistency can be achieved between updated results and measurements. The proposed method is computationally efficient.