Improvement of Springback Prediction Accuracy by Considering Nonlinear Elastoplastic Behavior after Stress Reversal

Abstract Prediction of springback during press forming has become more important due to the recent trend of application of high strength steels in automotive white body parts. The accuracy of springback prediction depends on the estimation of recovery strain after die release. As it is well known that unloading behavior after pre-strain shows a nonlinear stress-strain relationship, a material model which considers nonlinear elastoplastic behavior is necessary for accurate springback prediction. In this study, the nonlinear behaviors of high strength steel sheets under uniaxial and biaxial stress states were measured. A new material model that considers nonlinear behavior was proposed and implemented in finite element method (FEM) software. Press-forming tests of curved hat-shaped parts and the corresponding springback analyses were performed, and the springback angles were evaluated. The springback predictions made using the proposed model showed good agreement with the experimental results.