Multilevel Design Optimization of Automotive Structures Using Dummy- and Vehicle-Based Responses

A computationally efficient multilevel decomposition and optimization framework is developed for application to automotive structures. A full scale finite element (FE) model of a passenger car along with a dummy and occupant restraint system (ORS) is used to analyze crashworthiness and occupant safety criteria in two crash scenarios. The vehicle and ORS models are incorporated into a decomposed multilevel framework and optimized with mass and occupant injury criteria as objectives. A surrogate modeling technique is used to approximate the computationally expensive nonlinear FE responses. A multilevel target matching optimization problem is formulated to obtain a design satisfying system level performance targets. A balance is sought between crashworthiness and structural rigidity while minimizing overall mass of the vehicle. Two separate design problems involving crash and crash+vibration are considered. A major finding of this study is that, it is possible to achieve greater weight savings by including dummy-based responses in optimization problem

Multilevel design optimization of automotive structures using dummy- and vehicle-based responses

A computationally efficient multilevel decomposition and optimization framework is developed for application to automotive structures. A full scale finite element (FE) model of a passenger car along with a dummy and occupant restraint system (ORS) is used to analyze crashworthiness and occupant safety criteria in two crash scenarios. The vehicle and ORS models are incorporated into a decomposed multilevel framework and optimized with mass and occupant injury criteria as objectives. A surrogate modeling technique is used to approximate the computationally expensive nonlinear FE responses. A multilevel target matching optimization problem is formulated to obtain a design satisfying system level performance targets. A balance is sought between crashworthiness and structural rigidity while minimizing overall mass of the vehicle. Two separate design problems involving crash and crash+vibration are considered. A major finding of this study is that, it is possible to achieve greater weight savings by including dummy-based responses in optimization problem

Design of lightweight magnesium car body structure under crash and vibration constraints

Car body design in view of structural performance and lightweighting is a challenging task due to all the performance targets that must be satisfied such as vehicle safety and ride quality. In this paper, material replacement along with multidisciplinary design optimization strategy is proposed to develop a lightweight car body structure that satisfies the crash and vibration criteria while minimizing weight. Through finite element simulations, full frontal, offset frontal, and side crashes of a full car model are evaluated for peak acceleration, intrusion distance, and the internal energy absorbed by the structural parts. In addition, the first three fundamental natural frequencies are combined with the crash metrics to form the design constraints. The wall thicknesses of twenty-two parts are considered as the design variables. Latin Hypercube Sampling is used to sample the design space, while Radial Basis Function methodology is used to develop surrogate models for the selected crash responses at multiple sites as well as the first three fundamental natural frequencies. A nonlinear surrogate-based optimization problem is formulated for mass minimization under crash and vibration constraints. Using Sequential Quadratic Programming, the design optimization problem is solved with the results verified by finite element simulations. The performance of the optimum design with magnesium parts shows significant weight reduction and better performance compared to the baseline design