Artificial intelligence helps design an ultra-aerodynamic bike

July 12, 2018 by Cécilia Carron, Ecole Polytechnique Federale de Lausanne

Thanks to software developed by Neural Concept, an EPFL spin-off, bicycle engineers can quickly calculate the most aerodynamic shape for a bike. The software – which is being presented in Stockholm today at the International Conference on Machine Learning – applies artificial intelligence to a set of user-defined specifications. Engineers have already used the program to design a bike that they hope will break the world speed record this fall in Nevada.

The current record for a bicycle travelling across flat road is 133.78 km/h, set in 2012 by a Dutch team at the World Human Powered Speed Challenge, which takes place every year in the Nevada desert. But this September, a team from IUT Annecy aims to beat that record. The team used artificial-intelligence-based software developed by Neural Concept, an EPFL startup, to boost the performance of its bike. In just a few minutes, Neural Concept's technology can calculate the optimal shape of a bike to make it as aerodynamic as possible. It can also be used for aerodynamics calculations in a number of other applications. The company is presenting its software in Stockholm today at the International Conference on Machine Learning.

From the outside, the IUT Annecy team's recumbent bike looks more like a tiny racecar than a human-powered bicycle. It was custom-made to fit closely to the cyclist's body. During the Challenge, he will have to ride down a 200-meter stretch of straight, flat road as fast as possible, after a run-up of 8 km. The design objective clearly isn't cyclist comfort, but making the most out of every inch of the vehicle.

Credit: Ecole Polytechnique Federale de Lausanne
Coming up with faster, more detailed and more effective designs

Existing aerodynamic methods require an enormous amount of computing power. Traditionally bicycle engineers think up different forms and then test them using computer simulation. But here, for the first time, engineers employed optimization software – rather than their own intuition – to define the recumbent bike fairing. The IUT Annecy team used Neural Concept's software, specifying the bike's maximum length and width and the space needed for the drivetrain and wheels. The program then sorted through all kinds of shapes, quickly comparing them in order to come up with the best one. For instance, the program helped the engineers determine the best location for the vehicle's maximum width.

To develop the technology behind the software, researchers at EPFL's Computer Vision Laboratory trained a to calculate the aerodynamic properties of various forms represented by generic polygon meshes, which are collections of points used to generate 3-D shapes. This type of works by running through several layers, categorizing information from the simplest to the most complex. In the initial layers, the program identifies a shape's contours; then it assigns the contours to an object and determines what category the object belongs to based on the expected outcome.

Engineers can use the software to carry out detailed analyses of different designs more rapidly and with better accuracy. "Our program results in designs that are sometimes 5–20% more aerodynamic than conventional methods. But even more importantly, it can be used in certain situations that conventional methods can't," says Pierre Baqué, CEO of Neural Concept. Another benefit is that the software can compare designs without human bias. "The shapes used in training the program can be very different from the standard shapes for a given object. That gives it a great deal of flexibility," adds Baqué.

The World Human Powered Speed Challenge is a competition involving bicycles designed by teams of university students. This year it will take place on 10–15 September, and many other teams will also be gunning for the record. The Challenge will be a real-world test for both the IUT Annecy team and Neural Concept's machine-learning technology. The software has myriad other potential applications too, such as for designing drones, wind turbines and aircraft. Other industry professionals clearly see its potential – Baqué has been invited to speak at the world's biggest conference today in Stockholm. IUT Annecy and Neural Concept have already started working on the bike for next year's race. It will be designed exclusively and entirely by the , without any human intervention.

Explore further: A new brain-inspired computer takes us one step closer to simulating brain neural networks in real-time

Related Stories

Training artificial intelligence with artificial X-rays

July 6, 2018

Artificial intelligence (AI) holds real potential for improving both the speed and accuracy of medical diagnostics. But before clinicians can harness the power of AI to identify conditions in images such as X-rays, they have ...

Human-powered speedbike in Nevada challenge breaks record

September 19, 2015

The AeroVelo Eta, presented by VisualUnity, is a speedbike making news this week. Eta's makers have been working toward a dream of seeing their Eta break the speed record. Fans saw it last year at the World Human Powered ...

Recommended for you

A decade on, smartphone-like software finally heads to space

March 20, 2019

Once a traditional satellite is launched into space, its physical hardware and computer software stay mostly immutable for the rest of its existence as it orbits the Earth, even as the technology it serves on the ground continues ...


Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.