Robust optimization of an automobile rearview mirror for vibration reduction

Abstract

An automobile outside rearview mirror system has been analysed and designed to reduce vibration with a finite element model. Modal analysis is conducted for the calculation of natural frequencies. Harmonic analysis is utilized to estimate the displacements of the glass surface under dynamic loads. The model is verified with the vibration experiment for the parts and the assembled body. The structure of the mirror system is optimized for robustness defined by the Taguchi concept. At first, many potential design variables are defined. Final design variables are selected based on the amount of contribution to the objective function. That is, sensitive variables are chosen. The signal-to-noise (S/N) ratio in the Taguchi method is replaced by an objective function with mean and standard deviations of the quality characteristics. The defined objective function is appropriate for structural design in that the vibration displacements are minimized while the robustness is improved.

Discrete thickness optimization of an automobile body by using the continuous-variable-based method

“…Chen et al [2] optimized the shape of a fuel tank, and Leiva et al [3] introduced size optimization to determine the location of weld points. Hwang et al [4] designed a rear-view mirror with enhanced dynamic performance by using shape optimization whose design parameters are determined by the Taguchi method. Kim et al [5] improved the fatigue life of a lower control arm by using the design of experiment approach.…”

Model reduction techniques for dynamics analysis of ultra-precision linear stage

“…Compared with them, finite element analysis is more accurate than the multi-body system; however, it costs much more in terms of computer resources [1][2][3]. Model reduction techniques seek approximate solutions for the problem with many degrees of freedom within a subspace of small dimension.…”

Adaptive Modeling of Vehicle Mirror Vibrations by Predictive Compensation

“…This method of calculating the static ARIMA model was implemented using vibration signals from the database. It was found that for a variety of on-road signals a model of order [4,1,4] provided the best overall predictive performance while maintaining a satisfying computational efficiency.…”

“…The recursive ARIMA algorithm adapts the prediction model in real time to the changes in the vibration pattern. In the algorithm applied, eight parameters of the ARIMA [4,1,4] model are estimated at every sample time.…”

“…The baseline designs of mirrors are consequently modified to minimise the dominant vibration modes. Further statistical methods have been applied to increase the robustness of the mirror optimization process [4]. Within constraints of cost and manufacturing, the state of the art in design and manufacturing of car mirrors seems to have reached a relatively high level.…”