Multi-objective Reliability-Based Design Optimization for Energy Absorption Components Considering Manufacturing Effects

Light weight and crashworthiness design have been two main challenges in the vehicle industry, which often conflict with each other. To achieve light weight while improving the crashworthiness, design optimization techniques have been widely used. However, traditional crashworthiness design and process optimization are always performed respectively. That is, few process requirements are considered in the crashworthiness design which may lead to non-optimal or even impractical process scheme, and vice versa. Meanwhile, most of the energy absorbing members in vehicle body are fabricated by stamping process which will cause non-uniform thickness, residual strains and stresses, especially for high strength steel or advanced high strength steels. Furthermore, the uncertainties of the material properties, process and geometry generally propagate from process to crashworthiness responses, which will lead the uncontrollable fluctuations of crashworthiness. In other words, a deterministic optimization could lead to unreliable or unstable designs. To address these issues, a multi-objective reliability-based design optimization coupled process-performance (MORBDOCP) was proposed to optimize the double-hat thin-walled structure (DHTS). First, a finite element-based sequential coupled process-performance approach was developed to simulate the forming and crashworthiness of the DHTS, in which the material properties, process parameters and component geometry can be coupled and propagated from forming simulations to crashworthiness simulations efficiently. Then, the metamodel technologies were adopted to approximate the forming and crashworthiness responses. Finally, the multi-objective particle swarm optimization (MOPSO) approach, coupled with Monte Carlo Simulation (MCS), was employed to seek optimal reliability solutions. The optimal results show that the proposed method not only significantly improved the formability and crashworthiness, but also was capable of enhancing the reliability of Pareto solutions.