PSI - Issue 38

Denis Chojnacki et al. / Procedia Structural Integrity 38 (2022) 362–371 Author name / Structural Integrity Procedia 00 (2021) 000 – 000

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5. Conclusions Contrary to a highly regulated industry such as the aeronautics, the automotive industry is responsible for the up to-date standards used to design vehicles safely. In this paper, we have briefly summarize the current methodology to ensure mechanical reliability. It relies heavily upon RLDA both on our PG and on open roads. For the latter, we face increasing challenges. We have to transition from the historical expansive time-consuming unbiased RDLA campaign with a fully instrumented car to the futuristic millions of connected vehicles that could provide theoretically real-time continuous load histories measured by cheaper sensors. Meanwhile, we use biased RDLA to help us developing our methodologies including MBS and twin numerical models to optimize the vehicle instrumentation, a more complex definition of customer usage, bias integration in our models, supervised labelling algorithms and edge computing reduction algorithms. With all the new sensors required for more customer technical benefits, we have a real opportunity to generate statistically representative tails distribution of certain loading variables even if there are not the exact variables we are used to. However, with so much data made available, we have to develop the adapted big data algorithms to capitalize the information into useful ones. It is also a new challenge for our Structural Durabilty team who have to work closely with Electronic team in order to make Edge Computing inside vehicle not to overtake CAN flow limitations and to ensure availability of the data for the mechanical design process for a reasonable price. References Baroux E. & al, 2021. Analysis Of Real-Life Multi-Input Loading Histories For The Reliable Design Of Vehicle Chassis in: Fatigue Design Proceedings 2021. Bellec E. & Al, 2021. Multiaxial Variable Amplitude Loading for Automotive Parts Fatigue Life Assessment: A Loading Classification-based Approach Proposal in: Fatigue Design Proceedings 2021. Bignonnet, A., Thomas, J.J., 2001. Fatigue assessment and reliability in automotive design, in: SAE Brasil International Conference on Fatigue, SAE International Chojnacki, D., Pons S. , 2015. Dispositif d’analyse de l’ état de voies de circulation de véhicules automobiles, Patent FR3011793(A1) Débarbouillé A. & al 2021. Wheel forces estimation with an Augmented and Constrained Extended Kalman Filter applied on a nonlinear multi body model of a half vehicle in: Fatigue Design Proceedings 2021. ISO 2631-1, Standard 1997. Vibrations et chocs mécaniques- Evaluation de l’exposition des individus à des vibrations globales du corps, Johannesson, P. & Speckert, M. (Ed.), 2014. Guide to load analysis for durability in vehicle engineering. John Wiley & Sons, Ltd. Lipson, C., Sheth, N.J., Disney, R.L., 1967. Reliability prediction - Mechanical stress/strength interference. Technical Report. University of Michigan. Raoult, I., Delattre, B., 2020. Equivalent fatigue load approach for fatigue design of uncertain structures. International Journal of Fatigue. Thomas, J., Perroud, G., Bignonnet, A., Monnet, D., 1999. Fatigue design and reliability in the automotive industry, in: Marquis, G., Solin, J. (Eds.), Fatigue Design and Reliability. Elsevier. volume 23 of European Structural Integrity Society, pp. 1 – 11.