Create an Aero Map and Elevate Your Skills Today!

An aero map is an invaluable tool in every person’s engineering arsenal. Particularly if you are after a competitive edge in your race-car aerodynamic setup or you are just building a lap-simulation. Equally an aero-map is super helpful if you’re wanting to understand how your vehicle’s performance varies in real world conditions.

Firstly, what is an aero map? An Aero map provides detailed information on how the aerodynamic performance of a vehicle varies as its attitude changes. It will nearly always include front and rear ride height, but can be extended to include yaw, roll, steer and wing angle settings.

Generating an aero-map couldn’t be simpler, thanks to bramble’s kinematics models and Mappings feature. Additionally, creating the mappings comes at no extra cost!

Unfortunatley, fully populating an aero-map can involve a large number of simulations, especially if there are multiple input parameters, such as front/rear ride height, yaw, roll and steer. For this reason engineers will run a reduced set of simulations and then interpolate between the data points.

A design of experiments

The aero map generation begins by running an initial set of simulations made up of different combinations of your map parameters (for example, front and rear ride height). These runs are known as a Design of Experiments, or DoE.

bramble can help generate the DoE using the ‘Optimised Latin Hypercube’ option in the Map editor. This method produces an even distribution of attitudes throughout the design space helping improve the accuracy of the surrogate models.

Generating the aero maps

Aero maps are generated from the Mappings view, so select this view on the left-hand-side of the page. Simply give the map a name, select which run(s) we want to include, which parameters we altered and what performance measures we want to analyse.

The outputs can be viewed once the mappings have generated. Initially, this view will show the results from the DoE, but we can add to this by using the various prediction tools.

These include:

Predict a single design’s performance
Forecast the performance of a sweep of designs
Optimise for a design that yields a minimum or maximum performance
Visualise the data using contour, Pareto or cloud plots

What is a Pareto?

A really useful method of understanding an aero-map is by looking at how different performance measures trade-off against each other. For example, how much does aero-balance shift with increasing downforce? In essence, the Pareto plot is designed to show you this.

The performances of a large number of designs are extracted from the surrogate models and then plotted on a graph, with one performance measure on the x-axis, and a second on the y-axis. This graph then shows both the range of performances that can be achieved by adjusting your input parameters, and also how one performance varies with another.

aero mapping plot of total drag against total downforce

Extending the aero map

The surrogate models are a best attempt at predicting how performance might vary. Consequently, there will always be a certain amount of uncertainty in the accuracy of the model. However, the Mapping view gives the ability to visualise this uncertainty and so identify where we might want to add additional simulations to improve the quality of the mapping.

bramble is designed to make your life easy, so once you’ve identified the regions that you might want to refine, or indeed an interesting result that you’d like to investigate further, then ‘clicking’ on the plot will include the design in the results table. From here, you can select to add this point to a Map, which can then be used to launch your next simulation.