Design Optimization of Vehicle Body NVH Performance Based on Dynamic Response Analysis

Paper #:
  • 2017-01-0440

Published:
  • 2017-03-28
DOI:
  • 10.4271/2017-01-0440
Citation:
Lu, J., Zhan, Z., Song, H., Liu, X. et al., "Design Optimization of Vehicle Body NVH Performance Based on Dynamic Response Analysis," SAE Technical Paper 2017-01-0440, 2017, doi:10.4271/2017-01-0440.
Pages:
8
Abstract:
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.
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