After a competitive edge in your race-car aerodynamic setup? Building a lap-simulation? Or wanting to understand how your vehicle’s performance varies in real world conditions? Then an aero-map is an invaluable tool in your engineering arsenal.
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.
With bramble’s kinematics models and new Mappings feature, generating an aero-map couldn’t be simpler. And best of all, creating the mappings comes at no extra cost!
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. Consequently, engineers will run a reduced set of simulations and then interpolate between the data points.
A Design of Experiments
The generation of an aero-map begins by running an initial set of simulations made up of different combinations of your map parameters (front and rear ride height for example). 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
The aero-maps can be generated from the Mappings view. We simply need 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
- Predict 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?
Looking at how different performance measures trade-off against each other is a really useful method of understanding an aero-map. For example, how much does aero-balance shift with increasing downforce? 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 shows both the range of performances that can be achieved by adjusting your input parameters, and also how one performance varies with another.
Extending the Aero-Map
The surrogate models are a best attempt at predicting how performance might vary. Nevertheless, there will always be a certain amount of uncertainty in the accuracy of the model. 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 where regions that you might want to refine, or indeed an interesting result that’d you 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.