Lal Akin
Data-Driven Vehicle Performance Optimization for Formula Student Racing.
Rel. Andrea Tonoli, Stefano Favelli, Dario Salza, Federico Oldani. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024
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Abstract
In the world of motorsports, every driver aims for one thing: to finish with the fastest time. But it's not as simple as hitting the throttle pedal. There are vast numbers of factors involved, from how drivers handle their cars individually to the unpredictable nature of the track and vehicle. Formula Student Racing, where teams are tasked each year to build and race their own cars, is a university level single-seater competition. It's a hands-on learning experience like no other, where students apply classroom knowledge to real-world challenges, pushing the boundaries of automotive technology. Building a fast car is only part of the equation for Squadra Corse PoliTo, the student racing team of Politecnico di Torino.
The real challenge lies in integrating and optimizing driver and car performance, which is the main focus of this thesis
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