Projecte llegit
Títol: FSAE aerodynamics and lap time simulator
Estudiants que han llegit aquest projecte:
BATANERO RAMÍREZ, RUBÉN (data lectura: 12-09-2022)- Cerca aquest projecte a Bibliotècnica
- BATANERO RAMÍREZ, RUBÉN (data lectura: 12-09-2022)
- Cerca aquest projecte a Bibliotècnica
BATANERO RAMÍREZ, RUBÉN (data lectura: 12-09-2022) BATANERO RAMÍREZ, RUBÉN (data lectura: 12-09-2022)Director/a: VILLARDI DE MONTLAUR, ADELINE DE
Departament: FIS
Títol: FSAE aerodynamics and lap time simulator
Data inici oferta: 14-12-2021 Data finalització oferta: 14-07-2022
Estudis d'assignació del projecte:
- DG ENG AERO/SIS TEL
| Tipus: Individual | |
| Lloc de realització: EETAC | |
| Segon director/a (UPC): VALERO GARCÍA, MIGUEL | |
| Paraules clau: | |
| Formula Student, FSAE, Vilanova Formula Team, Genetic Algorithm, Neural Network, Deep Learning, Aerodynamics, CFD, Solidworks Flow Simulation, Unity | |
| Descripció del contingut i pla d'activitats: | |
| This TFG is developed within the context of the Formula Society
of Automotive Engineering (FSAE) contest to create a high- performance formula student car. Aerodynamic studies of a formula-style car are performed with SolidWorks comparing 3 different levels of difficulty: a basic design based on intuition, a design based on CFD results but with manufacturing limitations, and a complex design to achieve maximum efficiency. In order to translate the aerodynamic results into its equivalent best lap time in a certain circuit, a 3D simulator is built using Genetic Algorithms and Neural Networks. |
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| Overview (resum en anglès): | |
| Aerodynamic design of a Formula Student racing car using Solidworks Flow Simulation. The devices designed are compatible with the Vilanova Formula Team 2022 racing car.
The project also contains the development of a deep learning tool to test the track efficiency of the car. This tool compares different aerodynamic configurations in a determined track before building the car. |
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