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Weight Reduction of Double Wishbone-Arm Component in the Suspension System of an Automobile using Generative Design
Technical Paper
2021-28-0258
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
This work uses the Generative Design approach to achieve a weight reduction of the wishbone arm used in the vehicle suspension system. The suspension system of Haynes Roadster an open two-seater club racing car is taken for this study. Detailed calculations were done to understand the dynamic loads acting in the wishbone arm during acceleration, braking, and cornering. The above-calculated loads, material, domain, fabrication techniques are used as design parameters and weight reduction as the objective in the Generative design to obtain a final output. The various design iterations will be proposed by the algorithm based on the parameters and objectives defined. Generative design uses a machine learning approach which is time-saving and also eliminates the need for redoing and refining the initial designs by giving us optimum designs based on our usage as well as manufacturing requirement at the early stage. Different models created by Generative Design are then compared with the weight of the standard component and a suitable design is selected. The selected model is further validated by employing static stress simulation as well as using Fatigue testing in ANSYS Workbench.
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Citation
P G, S., Elsen, R., V, V., and B, B., "Weight Reduction of Double Wishbone-Arm Component in the Suspension System of an Automobile using Generative Design," SAE Technical Paper 2021-28-0258, 2021, https://doi.org/10.4271/2021-28-0258.Data Sets - Support Documents
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References
- Caetano , I. , Santos , L. , and Leitão , A. Computational Design in Architecture: Defining Parametric, Generative, and Algorithmic Design Frontiers of Architectural Research 9 2 2020 287 300 10.1016/j.foar.2019.12.008
- Oh , S. , Jung , Y. , Kim , S. , Lee , I. et al. Deep Generative Design: Integration of Topology Optimization and Generative Models Journal of Mechanical Design 141 11 2019 https://doi.org/10.1115/1.4044229
- Minaker , B.P. Fundamentals of Vehicle Dynamics and Modelling: A Textbook for Engineers With Illustrations and Examples (Automotive Series) 1st Wiley 2019
- R. S. Design Analysis of Double Wishbone Suspension International Journal of Research in Engineering and Technology 03 15 2014 874 876 https://doi.org/10.15623/ijret.2014.0315165
- Attia , H.A. Dynamic Modelling of the Double Wishbone Motor-Vehicle Suspension System European Journal of Mechanics - A/Solids 21 1 2002 167 174 https://doi.org/10.1016/s0997-7538(01)01178-0
- Jin , J.Q. and Li , J.J. Kinematic Performance Analysis of the Double Wishbone Independent Front Suspension Advanced Materials Research 490-495 2012 348 354 https://doi.org/10.4028/www.scientific.net/amr.490-495.348
- Ubaidillah , J.W.W. , Aditra , R. , Alnursyah , R. Abdul , R.R. et al. Design Analysis of Formula Student Race Car Suspension System AIP Conference Proceedings 2018 https://doi.org/10.1063/1.5024110
- https://www.yokohamatire.com/tires
- https://www.yokohamatire.com/tires-101/how-to-select-a-tire-1/selecting-the-right-tire
- https://www.750mc.co.uk/formulae/locost.htm
- Yuan-chun , K. Fatigue Analysis of Suspension Control Arm Based on Road Spectrum IOP Conference Series: Materials Science and Engineering 538 2019 012062 https://doi.org/10.1088/1757-899x/538/1/012062