| With the rapid development of Chinese automobile industry, the ownership of vehiclesis increasing. High fuel price, energy saving, and emission reduction, these are the problemsthat all the auto companies have to face. Developing a fuel-efficient vehicle can show thecompanies’ ability of product development. While an auto is running, a quite part of fuel isused to overcome the aerodynamic drag (drag, for short), and the auto’s aerodynamic shapedirectly decides the drag’s value. So it’s necessary to optimize an auto’s shape.The traditional optimization process is an iterative one and it’s based on the engineer’sexperience. It consume large amounts of resources. In this paper, according to the actualaerodynamic shape designing process, an automatic optimization process was built withinthe methods of CAS, CFD and mesh morpher. The process was based on some commercialsoftwares. It aimed at reducing the car’s drag quickly in the styling phase. It was alsopossible to investigate the design variables’ effect on drag.The aerodynamic shape optimization work was based on a hatchback. After finishingthe initial design, the CAS engineer would supply a CAS model which could be used forCFD analysis. Firstly, the baseline CAS model was analyzed and two objects were got:1. themesh strategy was determined;2. eight body design variables were confirmed afteranalyzing the flow filed. Among these variables, the frontal body had fours and the rear bodyhad fours. The eight variables were: windshield angle, hood angle, approach angle, face arc,rear window angle, rear roof height, departure angle and tail scale.After confirming the design variables, the research on the frontal body variables’ effecton drag was carried out. The relationship between each variable and drag was described.According to the degree of the effect, among the four frontal variables, the face arc had theminimum effect on drag, so it wouldn’t be considered when the whole car was optimized.After optimizing the frontal shape, the drag decreased by5.64%. Then the research on the rear body variables’ effect on drag was carried out and therelation curve between each variable and relationship curves between each variable and dragwas built. Similarly, according to the degree of the effect, among the four rear variables, thevariable named departure angle which was defined in this article had the minimum effect ondrag. It wouldn’t be considered when the whole car was optimized. After optimizing the rearshape, the drag had7.21%reduction. Apparently, the rear shape’s optimization had a betterresult.Finally, the whole aerodynamic shape optimization was carried out on the base of thesix variables which were screened before. It should be noticed that there was interactionbetween frontal variables and rear variables and rear variables affected more than frontalones. The drag was finally decreased by10.34%and the design style wasn’t changed. Thisresult is satisfying.According to the process’s application, some conclusions were got:(1). The frontal variables did not have obvious interactions. However, the rear ones had.And the frontal ones had interactions between rear ones. These can be used by designers;(2). Among the eight variables, the face arc and departure angle had little effect on dragand the approach angle and rear roof had big effect. The rear variables had bigger effect.(3). The relationships between the design variables and drag were non-linear, except thewindshield angle. Drag decreased first and increased within the increasing of departure angle.When it was3°, the drag was minimum.(4). The choose of approximation should be based on specific conditions.(5). It could got a better result when considering both frontal and rear design vaeiables.The automatic optimization process proposed in this paper can help engineer reduce thedrag quickly and efficiently. This process was applied to a CAS model actually and the resultwas good. This process can be used in the actual automotive styling phase. |
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