Calibration and Validation of a Car Subframe Finite Element Model Using Frequency Responses
Paper in proceedings, 2015
A finite element model of a car front subframe has been calibrated against test data. Stepped-sine testing has been used to give frequency response function estimates on an ensemble of seemingly identical subframes. Therefore, the deviation between test data and simulation results can be compared in a meaningful way by the outcome of model calibration and cross-validation. Emphasis has been put on the preparation of the test pieces for high fidelity testing and on bettering the chances of getting a calibration outcome that provides insight into the physical processes that govern the subframe dynamics. The front subframe model has more than 200,000 degrees-of-freedom and 17 model calibration parameters. The efficiency of the calibration procedure under these conditions is reported. To achieve efficiency, a calibration with a smooth deviation metric is used together with a damping equalization method that eliminates the need for matching of experimental and analytical eigenmodes. The method is combined with surrogate model frequency response evaluation based on model reduction for increased speed. The Matlab based open-domain software tool FEMcali that employs the Levenberg-Marquardt minimizer with randomized starts has been used for calibration and an unregularized Gauss-Newton minimizer has been used in the cross-validation.
Large model calibration
FEM model validation
FEM model calibration