Reliability-based optimization of a novel negative Poisson's ratio door anti-collision beam under side impact

Abstract Anti-collision beam of front door has significant influence on occupant protection and side crashworthiness. In order to improve the comprehensive side impact performance of vehicle, this work proposes a novel negative Poisson's ratio (NPR) door anti-collision beam based on star-shaped cellular structural material, and optimizes it by a reliability-based optimization scheme. First, the parametric model of NPR anti-collision beam, vehicle model assembling NPR beam, occupant restraint system model and side collision model are established. Then, the basic mechanical properties of the NPR structure are investigated under considering the axial normal force, transverse shear force and bending moment of each rod, and the macro performance of NPR beam are analyzed. Next, a deterministic optimization integrating optimal Latin hypercube sampling (OLHS) method, response surface model (RSM) and NSGA-II algorithm is conducted to improve the performance of novel NPR beam. Finally, considering the uncertainties of design variables, a reliability-based optimization is further executed to enhance the robustness of the deterministic optimization by using Design for Six Sigma (DFSS) method. Simulation results show that the ultimate optimized NPR anti-collision beam can not only ameliorate driver's protection and side crashworthiness, but also ensure the reliability and lightweight effect.