Robust Design Optimization of a Bumper System at Volvo Cars

Anneli Högberg (Volvo Car Corporation), Martin Kroon (Royal Institute of Technology), Xin Li (Xdin Systems), Håkan Strandberg (EnginSoft Nordic)

: Figure 1: Low speed crashes represent more than 70% of the crashes and combined with very high costs for repairs make robust design optimization extremely important. The study focuses on the bumper beam shown to the right.

70% are low speed crashes According to a recent survey by Volvo Cars Brand Experience Centre, low speed crashes represent over 70% of the crashes today. Typically crashes up to approximately 15 km/h are categorized as low speed crashes and are often caused by accidents during parking, queuing and braking situations.

The components of the rear part of the car are highly integrated, making repairs very expensive. Therefore, both customers and insurance companies require that the damage of a low speed crash should be limited to a few components which are easy to replace. In order to minimize the damage to the car body, the rear bumper beam must be designed to absorb all the energy from a crash. Due to the complexity and cost of repairs, the optimization of the bumper system becomes a very important and challenging topic. Ever since its establishment, Volvo Car Corporation has put safety among its top priorities and recently a thesis work [1] on best practices for robust design optimization of a rear bumper beam was carried out.

: Figure 2: Driving backwards into a fixed barrier at 15 km/h, i.e. the Allianz test, without damaging the car body is one of the toughest requirements. The figure shows the CAE model built in ANSA. This model of a full vehicle was used for verification.

modeFRONTIER was used to automate the robustness study using LS-DYNA and METApost. In order to save computational cost, a submodel instead of a full vehiclemodel was used for the robustness and metamodel evaluations.
Overall the results were very promising, proving the potential of running robust design optimization on metamodels for crash simulations.
The initial robustness study also provided great value and insight into the dominant parameters and considerations regarding the FE simulations. The arithmetic mean and standard deviation for the stochastics simulations were improved for all studied outputs, e.g. for the ringframe the results were improved by about 50% and 20% respectively.

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