Automated generation of physical surrogate vehicle models for crash optimization
Source abstract
Abstract
A challenge in the design and optimization of vehicle structures is the high computational costs required for crash analysis. In this paper an automated model generation for simplified vehicle crash models is presented. The considered crash load cases are the US NCAP (100%, 56 km/h), the Euro NCAP (40%, 64 km/h) and the IIHS Small Overlap (25%, 64 km/h). The generation of the physical surrogate vehicle models is based on different sub-steps which were automated using a process chain. With this process chain it is possible to evaluate very efficiently the influence of structural modifications on the global crash behavior. During the model generation the crash behavior of the surrogate model is directly compared with the full vehicle model to enable a direct assessment of the model quality. Since the interface, where the model is cut, is an important factor for the obtained correlation, different interface positions were analysed. With obtained solutions it is possible to identify the interface position, which fulfils the required correlation by a given computational time. Additionally, the interface discretisation is analyzed to identify the model configuration with the highest correlation. This investigation was performed for three different vehicle models.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Cellular and Composite Structures · Transportation Safety and Impact Analysis · Vehicle Dynamics and Control Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (31)
Show source-provided references
1. Altair, RADIOSS: Sub-modeling (cut approach). http://www.altairuniversity.com/wp-content/uploads/2012/08/RADIOSS_CRASH_CUT_V05.pdf (2012)
2. Beeh, E.: Development of a novel crash-adaptive front-end structure for alternative driven vehicles. Ph.D. thesis, German Aerospace Center, ISSN 1434-8454, 2015
3. CCSA: Development & Validation of a Finite Element Model for the 2012 Toyota Camry Passenger Sedan. Georg Mason University, Faifax (2016). https://doi.org/10.13021/g8n8810.13021/g8n88 ↗
4. Deb, A., Srinivas, K.C.: Development of a new lumped-parameter model for vehicle side-impact safety simulation. J. Automobile Engineering, Proc. IMechE, Vol. 222, Part D, 2008. https://doi.org/10.1243/09544070jauto80110.1243/09544070jauto801 ↗
5. Du Bois, P., Chou, C.C., Fileta, B.B., Khalil, T.B., King, A.I., Mahmood, H.F., Mertz, H.J., Wismans, J.: Vehicle Crashworthiness and Occupant Protection. American Iron and Steel Institue, Michigan (2004)
6. Duddeck, F.: Multidisciplinary optimization of car bodies. Struct. Multidisc. Optim. 35, 375–389 (2008). https://doi.org/10.1007/s00158-007-0130-610.1007/s00158-007-0130-6 ↗
7. Duddeck, F., Wehrle, E.: Recent advances on surrogate modelling for robustness assessment of structures with respect to crashworthiness requirements. In: 10th European LS-DYNA Conference 2015, Würzburg, Germany, 2015
8. Fender, J.: Solution Spaces for Vehicle Crash Design. Ph.D. thesis, Technical University Munich, Chair of Computational Mechanics, Munich, Germany, 2013
9. Gandhi, U.N., Hu, S.J.: Data-based approach in modeling automobile crash. Int. J. Impact Eng. 16(1), 95–118 (1995). https://doi.org/10.1016/0734-743X(94)E0029-U10.1016/0734-743X(94)E0029-U ↗
10. Hilmann, J.: On the Development of a Process Chain for Structural Optimization in Vehicle Passive Safety. Ph.D. thesis, Technical University Berlin, 2009, URN: urn:nbn:de:kobv:83-opus-22605
11. Jonsén, P., Isaksson, E., Sundin, K.G., Oldenburg, M.: Identification of lumped paramter automotive crash models for bumper system development. Int. J. Crashworth. 14(6), 533–541 (2009). https://doi.org/10.1080/1358826090283726210.1080/13588260902837262 ↗
12. Kamal, M.M.: Analysis and Simulation of Vehicle to Barrier Impact, SAE Paper No. 700414, 197010.4271/700414 ↗
13. Kim, H.-S., Kang, S.-Y., Lee, I.-H., Park, S.-H., Han, D.-C.: Vehicle frontal crashworthiness analysis by simplified structure modeling using nonlinear spring and beam elements. Int. J. Crashworth. 2(1), 107–118 (1996). https://doi.org/10.1533/cras.1997.003810.1533/cras.1997.0038 ↗
14. Kim, C.H., Mijar, A.R., Arora, J.S.: Development of simplified models for design and optimization of automotive structures for crashworthiness. Struct. Multidisc. Optim. 22, 307–321 (2001). https://doi.org/10.1007/PL0001328510.1007/PL00013285 ↗
15. Klaiber, M.: Use of Innovative 3D Printing Technologies for Flexible Process Chaining, 2. Technologietag Hybrider Leichtbau, Stuttgart (2015)
16. Kodiyalam, S., Yang, R.J., Gu, L., Tho, C.-H.: Multidisciplinary design optimization of a vehicle system in a scalable, high performance computing environment. Struct. Multidisc. Optim. 26, 256–263 (2004). https://doi.org/10.1007/s00158-003-0343-210.1007/s00158-003-0343-2 ↗
17. Marler, R.T., Kim, C.-H., Arora, J.S.: System identification of simplified crash models using multi-objective optimization. Comput. Methods Appl. Mech. Eng. 195, 4383–4395 (2006). https://doi.org/10.1016/j.cma.2005.09.00210.1016/j.cma.2005.09.002 ↗
18. Mooi, H.G., Huibers, J.H.A.M.: Simple and effective lumped mass models for determining kinetics and dynamics of car-to-car crashes. Int. J. Crashworth. 5(1), 7–23 (2000). https://doi.org/10.1533/cras.2000.012010.1533/cras.2000.0120 ↗
19. NCAC, Extended Validation of the Finite Element Model for the 2007 Chevrolet Silverado Pick-Up Truck. The George Washington University, 2012
20. NCAC, Extended Validation of the Finite Element Model for the 2010 Toyota Yaris Passenger Sedan. The George Washington University, 2012
21. Pahlavani, M., Marzbanrad, J.: Crashworthiness study of a full vehicle-lumped model using parameters optimisation. Int. J. Crashworth. 20(6), 573–591 (2015). https://doi.org/10.1080/13588265.2015.106891010.1080/13588265.2015.1068910 ↗
22. Pawlus, W., Nielsen, J.E., Karimi, H.R., Robbersmyr, K.G.: Mathematical modeling and analysis of a vehicle crash. In: 4th European Computing Conference, Bucharest, 2010, pp. 194–199, ISBN: 978-960-474-178-6
23. Qin, Y.: A concept to design fleet compatible vehicles for real accident environments, Fortschritt-Bereichte VDI. Reihe 12, Verkehrstechnik/Fahrzeugtechnik, VDI Verlag, Düsseldorf, 2011, ISBN: 3183737124
24. Relou, J.: Methods for the development of crash-compatible vehicles, Berichte aus der Fahrzeugtechnik. Ph.D. thesis, Shaker, Aachen, 2000, ISBN: 382657804X
25. Schäffer, M., Münster, M., Sturm, R., Friedrich, H.E.: Development of an Optimised Side Crash Concept for the Battery-Electric Vehicle Concept Urban Modular Vehicle, vol. 14. LS-DYNA Forum, Bamberg (2016)
26. Schäffer, M., Sturm, R., Friedrich, H.E.: Methodological approach for reducing computational costs of vehicle frontal crashworthiness analysis by using simplified structural modelling. Int. J. Crashworth. (2017). https://doi.org/10.1080/13588265.2017.138963110.1080/13588265.2017.1389631 ↗
27. Schmidt, F., Pitzer, M.: Component Models of Vehicle Structures for Side Crash Load Case Calculation. Karosseriebautage, Hamburg (2012)
28. Schwanitz, P., Sankarasubramanian, H., Werner, S.W., Göhlich, D., Chawla, A., Mukherjee, S.: Methodology for Multiparamter Optimization During the Concept Phase for Crash Relevant Vehicle Structures, 9. Weimar Optimierungs- und Stochastiktage, Weimar (2012)
29. Stein, M.: Development of a methodology to improve the structural interaction in a car-to-car-frontal crash. Ph.D. thesis, Berlin, Germany, 2015
30. Sturm, R., Schäffer, M., Münster, M.: Development of a safe modular body structure for a battery electric driven urban vehicle. In: Progress in Mechanics and Materials in Design 2017. LusoImpress S.A. Progress in Mechanics and Materials in Design, 2017, Albufeira, Portugal, ISBN 978-989-98832-6-0
31. Weigert, D., Duddeck, F., Schluder, H.: Automatic Model Reduction by Exploitation of Knowledge from Pre-existing Simulations, vol. 13. LS-DYNA Forum, Bamberg (2014)