Calibration, Validation and Uncertainty Quantification of Nominally Identical Car Subframes
Paper in proceedings, 2016
In this paper a finite element model, with over half a million degrees-of-freedom, of a car front subframe has been calibrated and validated against experimental MIMO data of several nominally identical components. The spread between the individual components has been investigated and is reported. Sensor positioning was performed with an extended effective independence method, using system gramians to reject sensors with redundant information. The Fisher information matrix was used in the identification of the most significant model calibration parameters. Validation of the calibrated model was performed to evaluated the difference between the nominal and calibrated model, and bootstrapping used to investigate the validity of the calibrated parameters. The parameter identification, calibration, validation and bootstrapping have been performed using the open-source MATLAB tool FEMcali.