Widely used in automotive industry, lightweight metallic structures are a key contributor to fuel efficiency and reduced emissions of vehicles. Lightweight structures are traditionally designed through employing the material distribution techniques sequentially. This approach often leads to non-optimal designs due to constricting the design space in each step of the design procedure. The current study presents a novel Multidisciplinary Design Optimization (MDO) framework developed to address this issue. Topology, topography, and gauge optimization techniques are employed in the development of design modules and Particle Swarm Optimization (PSO) algorithm is linked to the MDO framework to ensure efficient searching in large design spaces often encountered in automotive applications. The developed framework is then further tailored to the design of an automotive Cross-Car Beam (CCB) assembly. Sensitivity study is performed to identify the major contributor parts to the CCB mass and performance. The optimized CCB is shown to meet the design requirements while the mass and cost are considerably reduced.


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    Title :

    PSO-Based Multidisciplinary Design Optimization of Automotive Assemblies


    Additional title:

    Sae International Journal of Passenger Cars. Mechanical Systems
    Sae Int. J. Passeng. Cars - Mech. Syst


    Contributors:


    Publication date :

    2017-08-01


    Size :

    12 pages




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English






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