Optimizing vehicle aerodynamics through the synergistic application of Design of Experiments (DoE) and Computational Fluid Dynamics (CFD)
DOI:
https://doi.org/10.54097/ns22b830Keywords:
Aerodynamic Analysis, Automotive Design, 3-D Modeling, Computational Fluid Dynamics, Design of Experiment, Drag Coefficient, Flow Trajectories.Abstract
The aerodynamic design of cars not only creates aesthetic and diverse car shapes, but also ensures their safety and fuel economy. According to Mustafa Cakir's research[1], approximately of the fuel consumption of a car traveling at high speeds is used to counteract air resistance. However, with the increasing severity of global warming, emissions standards for automobile exhaust are becoming increasingly stringent. Considering that gasoline vehicles still dominate the household car market, optimizing the aerodynamic design of automobiles is imperative. This work analyzes and optimizes the aerodynamic design of automobiles through the synergistic application of Design of Experiments (DoE) and Computational Fluid Dynamics (CFD). Before conducting experiments, the article first introduces and derives the basic control equations of computational fluid dynamics, namely the continuity equation and Navier-Stokes equation, and describes how they are used in experiments. Then, the article briefly introduces the drag coefficients of automobiles, which are important theoretical basis for subsequent aerodynamic design optimization in this article. In the experimental part, this study focuses on the influence of four important design parameters: angle of the front window , angle of the hood , angle of the back window , and length of the trunk . Using Solidworks 3D modeling software, the article simulates these design parameters and prepares for CFD numerical simulation by geometry, setting computational domain, boundary conditions, and objective functions, and generating mesh. Based on the DoE and numerical simulation results, the article ultimately selects a front window angle of , a hood angle of , a back window of , and as the optimized design. Compared with the basic model, the optimized model reduces the drag coefficient by about . The conclusion of this study provides ideas and theoretical basis for the aerodynamic optimization design of new generation automobiles with the incorporation of DoE. However, the design parameters of automobiles are countless, and in the future, this article will strive to research and simulate more diverse automobile designs and analyze their aerodynamic performance to explore more optimized designs.
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