How To Analyze Drag Racing Data
How To Analyze Drag Racing Data – Imagine yourself at a motorsports event with the deafening roar of the engines and the thrill of high speed. In the midst of this excitement, you notice a breathtaking moment of driving finesse as one car expertly hides behind another. This phenomenon is not just a spectacle; is the art of aerodynamic design, a key strategy in motorsports and racing that uses the laws of physics to reduce drag, increase speed and win on the track.
In this article, we will delve into the intricacies of drafting in racing, shedding light on how it works and the speeds at which it is most effective. We will also highlight the effects with a small CFD study using a simulation platform to visualize and capture the effects at various end distances.
How To Analyze Drag Racing Data
Drafting refers to a strategic racing technique in which a vehicle follows closely behind another, taking advantage of reduced air drag or the air drag produced by the leading vehicle. This aerodynamic phenomenon causes the following vehicle to experience a reduction in wind resistance, allowing it to achieve higher speeds or reduce fuel consumption compared to driving alone.
Formula 1 Corner Analysis
Sketching is also interchangeably referred to as slipstreaming. Pulling successfully requires a delicate balance between staying close to the lead vehicle and maintaining control, as too close can cause air turbulence and compromise stability.
Drawing uses a key principle of viscous fluid dynamics called “boundary layer separation.” This phenomenon occurs when the airflow over an object loses its ability to follow the contour of the object’s surface and separates from it, creating a turbulent and chaotic wake. This turbulent wake leads to a reduced pressure or vacuum at the rear of the vehicle, creating a drag force that opposes the vehicle’s motion and requires additional energy to overcome. The net effect is to reduce fuel (or electricity) consumption or, in the case of a racing car, reduce top speed.
As the next vehicle slips into this turbulent wake, its front end strengthens the wake, and the tandem vehicles will begin to behave more like a longer, single aerodynamic body. Depending on the distance between the vehicles, the footprint of the first car can be almost eliminated. Appropriate pressure changes reduce the drag force in both vehicles compared to driving alone (increased rear pressure in the leading vehicle and reduced front pressure in the trailing vehicle).
In this way, the entire convoy experiences significantly reduced air resistance, allowing it to achieve higher top speeds and greater fuel efficiency for the same power output. Adding more cars to the draft (as is typical at the Indianapolis 500 or a NASCAR superspeedway like Daytona or Talladega) can further enhance the effect for the entire platoon. In addition, the car behind can use drafting to gain a short-term acceleration to reach the target, which can be used to “slingshot” momentum to overtake the leading car after braking and entering a corner, as is common in F1.
Trading Card’ Representation Of Each Car’s Strengths And Weaknesses
Drag can also cause a very marked shift in the balance of aerodynamic forces. When you hear a race car driver say that he was in “dirty air” or “the air was taken out of his nose,” he is talking about a change in the balance of aerodynamic forces. Generally, the center of pressure (or neutral moment point) moves from front to rear (and possibly sideways and vertically) in response to the net pressure change caused by thrust. Moving too much rearward for the car behind will result in understeer. The leading car may see the opposite effect, with a reduction in the rear spoiler or underbody downforce, leading to oversteer.
Figure 3: Dirty air can affect F1 cars entering corners after drafting, so they must time their overtakes carefully. (Motor sports)
Aerodynamic efficiency is not the only consequence of “dirty air”. Providing adequate air cooling can often be a big problem for your next car. Drivers constantly exert pressure and expose mechanical components such as the engine and brakes to extreme temperatures. When the total air pressure (or capacity to do work) in the car behind decreases significantly, it begins to affect all cooling systems that were designed with “clean” airflow in mind; radiators will not work well enough, airflow through the brake ducts will be insufficient, cooling of EV batteries will be suboptimal, etc. All of this causes overheating, and drivers usually have to step back to manage these systems.
Figure 4: Side front duct of a 2023 Ferrari F1 car, showing where air enters to cool the car’s internal components (MAXF1net)
Drag Reduction By Application Of Aerodynamic Devices In A Race Car
The effectiveness of plotting depends on many factors, including the overall speed of the lead and follow vehicles, the spacing between them, and the shape of the vehicles involved. Drag is most severe at higher speeds, usually above 80 km/h. At these speeds, aerodynamic forces become more apparent and the advantages of drag become more apparent.
Let’s take a closer look at the drag force equation below. Here we see that drag is proportional to the square of speed, so a pair of race cars traveling at 200 miles per hour (~320 km/h) experience drag 16 times greater than a car traveling at highway speeds of 50 miles per hour (80 km/h) . This greatly increases the drag change resulting from dragging.
The overall aerodynamic shape of the vehicles and any aerodynamic devices (splitter, spoiler, wings, etc.) also greatly influence their towing ability. Racing vehicles are often highly dependent on the performance of these separate aerodynamic components, so increasing the perceived airflow can have a sudden and often undesirable effect on handling balance. This is especially true when cars are cornering and have limited traction. You can often hear drivers complaining about “dirty air”. Motorsport sanctioning bodies always examine aerodynamic packages and overall car designs to reduce this sensitivity as it makes competition and overtaking difficult.
In addition to vehicle shape and features, ground clearance and chassis design features (such as the diffuser) are also critical factors affecting towing performance. The low pressure suction created by the floor is very sensitive to the flow of air taken in and out. When a car follows another in a draft, the lead car effectively uses the energy of the oncoming air and leaves much less to fuel the performance of the trail car under the floor. Again, this can have a detrimental effect on handling balance and reduce the maximum grip available to the rear car when cornering.
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To gain deeper insight into the intricate dynamics of drafting, engineers have turned to computational fluid dynamics (CFD) simulations, usually rather than wind tunnel experiments. This choice is often due to the high cost of wind tunnels, but in this case the general physical size limitations of most wind tunnels prevent testing of many cars.
CFD provides a platform to accurately predict and analyze the behavior of tandem cars as they approach each other. You can examine the map of various relative positions to understand the effects of handling and take steps to optimize drawing performance. What’s more, engineers can understand why these changes are happening by visualizing airflow, which will accelerate car development and influence design changes. This powerful tool enables engineers and designers to predict the performance of their designs under various conditions and optimize them before hitting the track.
There are two different CFD modules on the platform that can be used to simulate the vehicle’s external aerodynamics and evaluate drafting performance. The Incompressible module uses a computationally efficient and practical finite-volume (FVM) approach, using the k-w Reynolds-averaged Navier-Stokes (RANS) turbulence model that is common in the industry. The second approach uses an advanced incompressible Lattice Boltzmann (LBM) method, which can quickly resolve high-quality turbulence transients by leveraging the power of GPUs.
Overall, LBM is the better option in terms of accuracy (especially at the rear of the vehicle), scalability, and geometry robustness. Currently, DES and IDDES turbulence modeling (implemented in the LBM solution) is considered state of the art for accurate simulation of vehicle external aerodynamics. However, if a quick early review is enough, a simplified model using the Incompressible RANS approach still has advantages.
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A drafting study was performed using geometry from the 2019 Formula 1 regulations, as shown in Figure 5. This geometry was imported from the dirty .stl surface mesh directly into the platform. The poor quality of this initial geometry is not a problem for LBM because it is able to handle non-manifold surface mesh geometries in this format.
First, a single car simulation was performed to obtain baseline values for the drag coefficients, lift (downforce), and lift balance, and the corresponding surface pressure plot. This “virtual wind tunnel” CFD simulation was performed at a speed of 180 mph (~290 km/h) and assumed that the road was rolling and the tires were spinning due to the rotational speed of the wall. The force factors are summarized in Table 1 below.
The vehicle was shown to have a relatively high drag coefficient ((C_D)) of 0.805, which is expected of a racing vehicle. The downforce was high