AbstractThe transition to electric vehicles is driving a fundamental shift in the automobile design process. Changes in constraints afforded by the absence of a combustion engine create new opportunities for modifying vehicle geometries. Current approaches to optimizing vehicle aerodynamics require a vast amount of computational studies and physical experiments, which are expensive when performing parameter sweeps over conceivable geometric configurations, suggesting the need for more efficient surrogate models to assist analysis. Here we analyze a dataset of industry-quality automobile geometries with their associated aerodynamic performance obtained from experimentally validated, high-fidelity large-eddy simulations. We show that a relationship between these geometries and their respective aerodynamics can be extracted in a low-dimensional manner by leveraging a nonlinear autoencoder which is simultaneously trained to estimate the drag coefficient from the latent variables. We perform aerodynamic design optimization of vehicle designs by making use of the learned aerodynamic relationship in the low-order space obtained by the model. We demonstrate that the aerodynamic trends for the geometries produced from the optimization process show agreement with validation simulations. The findings of this work demonstrate the application of data-driven approaches to the analysis and design of vehicles in a production environment.


    Access

    Download


    Export, share and cite



    Title :

    Aerodynamics-guided machine learning for design optimization of electric vehicles


    Additional title:

    Commun Eng


    Contributors:

    Published in:

    Publication date :

    2024-11-20




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Aerodynamics-guided machine learning for design optimization of electric vehicles

    Jonathan Tran / Kai Fukami / Kenta Inada et al. | DOAJ | 2024

    Free access


    Aerodynamics of road vehicles

    Schütz, Thomas | TIBKAT | 2016


    Aerodynamics of Commercial Vehicles

    Frank, Thorsten / Turney, James | Springer Verlag | 2015


    Unsteady Aerodynamics of Vehicles

    ANDREW G. HAMMIT | AIAA | 1975