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

Abstract

Springback prediction during press forming has become more important in the recent background that high-strength steels have been applied to white body parts. The springback prediction accuracy depends on the estimation of recovery strain after die release. It is well known that unloading behavior after pre-strain shows a nonlinear stress-strain relationship, so a material model considering the nonlinear elastoplastic behavior is necessary for accurate springback predictions. In this study, the nonlinear behaviors of high-strength steel sheets under uniaxial and biaxial stress states were measured. A new material model that takes the nonlinear behavior into consideration was proposed, and implemented into finite element method (FEM) software. The 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 experimental results.