Machine Learning Transformed the Porsche 919 Hybrid Evo

The history of Porsche Endurance Racing is one of the most exciting and successful and probably unparalleled by any. During the decades, legends like 917, 956, 911 GT1 collected victories on racetracks around the world. Among those, surely, the 24-hours of Le Mans is the absolute pinnacle. No other brand managed to collect as many overall victories as Porsche in this race.

Using Machine Learning for decisions

This is when we decided to use some of the machine learning algorithms to help us first with the choice of the correct design parameters. Similar like in picture processing, one can use the database of available airfoils (in our case about ~1600 airfoils, m-selig.ae.illinois.edu) and train the machine learning models with these (so-called dimensionality reduction). After this analysis, it turns out, that something like an “airfoil DNA” can be extracted from all the data and that each of possible airfoils can be described only by a relatively small number of “airfoil genes” (only 5 to 10 depending on desired precision). Therefore, if an engineer is looking for an optimal airfoil, it is enough only just to vary these few “airfoil genes”.

“We used the algorithms, that mimic the evolution process of the organisms in the nature and lead to the “fittest” one."

For full article: https://newsroom.porsche.com/en/porsche-digital/porsche-digital-919-hybrid-evo-technology-machine-learning-josef-dubsky-christos-pashias.html