In the development of electric SUV models, aerodynamic drag reduction is a critical factor for enhancing vehicle performance and energy efficiency. As an engineer focused on computational fluid dynamics (CFD), I have been involved in optimizing the tail fin design of an electric SUV to address challenges in drag coefficient stability and wake flow control. Aerodynamic drag constitutes a significant portion of total resistance at high speeds, with air resistance dominating above 60 km/h. For electric SUV vehicles, minimizing this drag directly translates to extended driving range and reduced energy consumption under standard cycles like the New European Driving Cycle (NEDC). This article details our approach using CFD simulations to analyze flow fields, implement optimization strategies, and achieve substantial improvements in the electric SUV’s aerodynamic profile.
The primary components of aerodynamic drag include pressure drag and friction drag, where pressure drag, influenced by vehicle shape, accounts for the majority. In SUV designs, the tail fin plays a pivotal role in managing airflow separation and controlling vortex structures at the rear. Traditional SUV tail fins, often referred to as rear spoilers, guide top airflow to delay separation and direct it in a manner that minimizes wake size. However, with the trend toward sportier electric SUV designs, floating tail fins have emerged as a popular alternative. These floating designs introduce openings at the front end, which can lead to instability in wake flow and fluctuations in the drag coefficient (Cd). Our investigation began with a baseline electric SUV model equipped with a conventional tail fin, where initial CFD analysis revealed suboptimal vortex patterns and elevated Cd values.
We employed transient CFD simulations using PowerFLOW software to model the airflow around the electric SUV. The baseline scenario showed that the tail fin’s upward curvature caused top airflow to deflect upward, leading to a large, unstable wake vortex. The bottom airflow, accelerated by the electric SUV’s flat underbody, separated at the rear bumper and interacted poorly with the top flow, exacerbating the vortex size. To quantify this, we analyzed the velocity distribution on the y=0 mm plane, where the wake structure appeared asymmetrical and inefficient. The drag coefficient for the baseline electric SUV was recorded as a reference, and we identified key areas for improvement, such as redirecting the top airflow downward to balance the upper and lower flow interactions.
Our first optimization step involved modifying the tail fin by pressing its end downward by 65 mm in the z-direction while keeping the x-direction unchanged. This adjustment aimed to alter the top airflow’s ejection direction, promoting a more balanced vortex and reducing the wake’s vertical extent. The CFD results demonstrated a notable improvement, with the Cd decreasing by 0.020. The velocity slices on the y=0 mm plane confirmed that the top airflow now descended, compressing the wake and enhancing stability. However, this design conflicted with the electric SUV’s stylistic requirements, prompting the adoption of a floating tail fin with a front opening. This floating design maintained the aesthetic appeal but introduced new challenges: airflow from the opening impinged on the rear window, creating low-pressure zones and asymmetric vortices that increased Cd sensitivity to minor changes, such as side mirror adjustments.
To address these issues, we conducted a series of parametric studies, summarized in Table 1, which outlines the simulation cases and their impacts on drag reduction. Each step involved incremental changes to the tail fin geometry, with CFD analyses evaluating the effects on flow field and Cd.
| Case No. | Description | Cd Change | Cumulative Cd Reduction |
|---|---|---|---|
| 1 | Baseline electric SUV with conventional tail fin | 0.000 | 0.000 |
| 2 | Floating tail fin with front opening | -0.020 | -0.020 |
| 3 | CAD model update for minor refinements | -0.005 | -0.025 |
| 4 | Side mirror optimization and tail fin bracket addition | +0.008 | -0.017 |
| 5 | Enlarged tail fin opening | +0.002 | -0.015 |
| 6 | Incorporated upward-curving feature at roof end | -0.007 | -0.022 |
| 7 | Optimized upward-curving feature geometry | -0.003 | -0.025 |
The aerodynamic drag force acting on the electric SUV can be expressed using the standard equation for drag: $$F_d = \frac{1}{2} \rho C_d A V^2$$ where \(F_d\) is the drag force, \(\rho\) is the air density, \(C_d\) is the drag coefficient, \(A\) is the frontal area, and \(V\) is the vehicle velocity. For the electric SUV, reducing \(C_d\) directly lowers \(F_d\), which in turn decreases the energy required for propulsion. The energy consumption under NEDC conditions can be modeled as: $$E = \int (F_d + F_r) V \, dt$$ where \(E\) is the energy consumption, \(F_r\) is the rolling resistance, and the integral is over the driving cycle. Our optimizations aimed to minimize \(C_d\), leading to a 7.2% reduction in drag coefficient and a 2.6% decrease in NEDC energy consumption for the electric SUV.
In the floating tail fin design, the front opening allowed top airflow to enter the rear window region, creating low-pressure zones and destabilizing the wake. We hypothesized that controlling this inflow was crucial. First, we enlarged the opening, which increased the inflow and worsened the low-pressure areas, raising Cd by 0.002. This confirmed that excessive airflow from the opening was detrimental. Next, we introduced an upward-curving feature at the roof end, just above the rear window, to force airflow separation and redirect it away from the window. This reduced Cd by 0.007 by stabilizing the vortex structure. Further refinements to this feature yielded an additional Cd drop of 0.003, resulting in a total reduction of 0.025 from the baseline. The final optimized floating tail fin for the electric SUV demonstrated a balanced wake with minimal asymmetry, as seen in velocity slices and surface pressure distributions.
To delve deeper into the flow mechanics, we analyzed the wake topology using surface streamlines and pressure contours. In one data update, the wake transitioned from a stable square-back pattern to a notchback-like structure, where separated flow from the roof formed large recirculating vortices that impinged on the rear window. This phenomenon, akin to the “hairpin vortices” described in literature for notchback cars, involved interactions between C-pillar vortices and the incoming flow, leading to periodic vortex shedding and increased low-pressure zones. The surface pressure on the rear window showed significant asymmetry, with one side experiencing a pronounced drop in pressure. This instability highlighted the sensitivity of the electric SUV’s wake to geometric perturbations, particularly with the floating tail fin design.
We derived a theoretical model to describe the vortex stability, based on the Reynolds number and Strouhal number for vortex shedding: $$St = \frac{f L}{V}$$ where \(St\) is the Strouhal number, \(f\) is the vortex shedding frequency, \(L\) is a characteristic length (e.g., tail fin width), and \(V\) is the velocity. For the electric SUV, changes in tail fin geometry altered \(L\) and the flow separation points, affecting \(St\) and the wake coherence. The pressure coefficient \(C_p\) on the rear surface is given by: $$C_p = \frac{p – p_{\infty}}{\frac{1}{2} \rho V^2}$$ where \(p\) is the local pressure and \(p_{\infty}\) is the freestream pressure. Optimizations that reduced the magnitude of negative \(C_p\) on the rear window contributed to drag reduction.
Based on our findings, we proposed two general strategies for electric SUV tail fin optimization: partial blocking of the tail fin openings to limit inflow and lengthening C-pillar strakes to disrupt vortex interactions. These approaches can enhance wake stability without compromising design aesthetics. In conclusion, our work on the electric SUV tail fin optimization achieved a 7.2% reduction in Cd and a 2.6% improvement in NEDC energy efficiency, underscoring the importance of tailored aerodynamic designs for future electric SUV models. The integration of CFD simulations with iterative geometric changes proved effective in resolving wake instability issues, providing a valuable framework for similar projects in the automotive industry.
Further research could explore dynamic simulations under crosswind conditions or incorporate machine learning for rapid optimization of tail fin shapes. As electric SUV adoption grows, such aerodynamic refinements will play an increasingly vital role in maximizing range and sustainability.