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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    Titel :

    Weight Reduction of Double Wishbone-Arm Component in the Suspension System of an Automobile using Generative Design


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    B, Beno Prince (Autor:in) / Elsen, Renold (Autor:in) / P G, Sachin (Autor:in) / V, Vijayaragavan (Autor:in)

    Kongress:

    International Conference on Advances in Design, Materials, Manufacturing and Surface Engineering for Mobility ; 2021



    Erscheinungsdatum :

    2021-10-01




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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