Aerodynamic Shape Optimization Method of Non-Smooth Surfaces for Aerodynamic Drag Reduction on A Minivan

Abstract

To reduce aerodynamic drag of a minivan, non-smooth surfaces are applied to the minivan’s roof panel design. A steady computational fluid dynamics (CFD) method is used to investigate the aerodynamic drag characteristics. The accuracy of the numerical method is validated by wind tunnel test. The drag reduction effects of rectangle, rhombus and arithmetic progression arrangement for circular concaves are investigated numerically, and then the aerodynamic drag coefficient of the rectangle arrangement with a better drag reduction effect is chosen as the optimization objective. Three parameters, that is, the diameter D of the circular concave, the width W and the longitudinal distance L among the circular concaves, are selected as design variables. A 20-level design of an experimental study using a Latin Hypercube scheme is conducted. The responses of 20 groups of sample points are obtained by CFD simulation, based on which a Kriging model is chosen to create the surrogate-model. The multi-island genetic algorithm is employed to find the optimum solution. The result shows that maximum drag reduction effects up to 7.71% can be achieved with a rectangle circular concaves arrangement. The reduction mechanism of the roof with the circular concaves was discussed. The circular concaves decrease friction resistance of the roof and change the flow characteristics of the recirculation area in the wake of the minivan. The roof with the circular concaves reduces the differential pressure drag of the front and rear of the minivan.

Numerical Analysis and Optimization of the Front Window Visor for Vehicle Wind Buffeting Noise Reduction Based on Zonal SAS k-ε Method

“…Meanwhile, as R and L2 increase, P increases and then decreases. The kriging model can reduce the computational cost of performing optimization [26]. According to the optimal Latin hypercube design of experiments in Table 2 and the CFD results in Figure 9, the kriging model was used to establish an approximation model of the response relationship between the design variables and the optimization objective.…”

Optimizing Building Orientation and Roof Angle of a Typhoon-Resilient Single-Family House Using Genetic Algorithm and Computational Fluid Dynamics

“…CFD-based numerical modeling and GA-based optimization are integrable strategies used to generate highly recommendable designs for various technological products such as photovoltaic panel arrays [27], automobiles [28,29], wind turbines [30][31][32][33], unmanned aerial vehicles [34], and other industrial machinery [35]. The combination of CFD and GA achieved a minimum aerodynamic lift force on the photovoltaic structure by searching for the best tilt angle and pitch values between two rows of solar panels [27].…”

“…The combination of CFD and GA achieved a minimum aerodynamic lift force on the photovoltaic structure by searching for the best tilt angle and pitch values between two rows of solar panels [27]. In the automobile industry, it is essential to continue improving the aerodynamic performance of vehicles through parametrizing geometries using GA [28,29]. In these investigations, the design goal was to lower the drag coefficient while considering rthe pressure constraints in the CFD simulations.…”

Aerodynamic design optimization of locally built FSR Isuzu bus through numerical simulation

“…Using numerical simulations, the impact of applying a non-smooth, dimpled surface to the rear slope of a generic vehicle body on the reduction of aerodynamic drag was examined. Yang et al [6] suggested incorporating non-smooth features into a minivan's roof panel design to reduce the vehicle's aerodynamic drag. The aerodynamic drag properties are investigated by a stable computational fluid dynamics (CFD) method.…”

“…Because aerodynamic features reduce air resistance during operation, they save fuel and improve driving stability against lift force and crosswind, which is important from an economic perspective [4]. Aerodynamic drag reduction can be achieved at a cheap cost to boost fuel economy, and shape optimization for low drag has become an essential component of the whole vehicle design process [3,5,6].…”