Pietro Chiavassa
A genetic algorithm for optimizing velocity in the Bridgestone World Solar Challenge.
Rel. Filippo Gandino, Dirk Roose, Dries Ketelslegers. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2020
|
Preview |
PDF (Tesi_di_laurea)
- Tesi
Licenza: Creative Commons Attribution Non-commercial No Derivatives. Download (2MB) | Preview |
Abstract
In the Bridgestone World Solar Challenge (WSC) student teams from various universities use solar technology and advanced engineering to create sustainable innovative solar powered electric vehicles able to travel 3,020 km from Darwin to Adelaide. During the race, the strategy unit of the teams must be able to decide at which speed the car should drive at any given moment. The objective is to finish the race in the least amount of time while avoiding the risk of running out of battery. The Belgian Team (Agoria Solar Team) uses a Genetic Algorithm to solve this problem. A population of possible solutions is evolved, in which individuals are represented as vectors of velocities that the car should drive at in each segment of the race.
A fitness function evaluates each solution by taking into account weather conditions, spatial position, topography information, car speed, car specifications and race specific constraints
Relatori
Anno Accademico
Tipo di pubblicazione
Numero di pagine
Corso di laurea
Classe di laurea
Ente in cotutela
Aziende collaboratrici
URI
![]() |
Modifica (riservato agli operatori) |
