An automatic model calibration method for occupant restraint systems

  • Authors:
  • Zhenfei Zhan;Yan Fu;Ren-Jye Yang;Yinghong Peng

  • Affiliations:
  • School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China 200240;Research and Advanced Engineering, Ford Motor Company, Dearborn, USA 48121;Research and Advanced Engineering, Ford Motor Company, Dearborn, USA 48121;School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China 200240

  • Venue:
  • Structural and Multidisciplinary Optimization
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

Computer models are widely used to simulate dynamic systems in automobile industry. It is imperative to have high quality CAE models with good predictive capability. This requires CAE engineers to conduct model calibration with physical tests. The challenges in the occupant restraint system model calibration are: (1) the dynamic system usually consists of multiple responses, (2) most of the responses are functional data or time histories, and (3) the traditional trial-and-error calibration approach is time consuming and highly depends on analyst's expertise. These call for the development of an automatic and effective model calibration method. This paper presents a newly developed automatic model calibration method, based on the Error Assessment of Response Time Histories (EARTH) metric. The EARTH metric is used to perform model assessment on various important features of the functional responses. A new multi-objective optimization problem is formulated and solved by a Non-dominated Sorting Genetic Algorithm to automatically update CAE model parameters. A real-world example is used to demonstrate the use of the proposed method.