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Development of an Adaptive Model Predictive Control for platooning safety in Battery Electric Vehicles

Antonio Capuano

Development of an Adaptive Model Predictive Control for platooning safety in Battery Electric Vehicles.

Rel. Daniela Anna Misul. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Meccanica, 2021

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Abstract:

soluzioni ADAS - ambito automotive Nowadays, the continuous improvement in transportation systems technologies provides several different opportunities which are exploited for the enhancement of safety and comfort in passenger vehicles. As an example, Adaptive Cruise Control (ACC) might provide benefits, including smoothness of the traffic flow and collision avoidance. In addition, Vehicle-to-Vehicle (V2V) communication may be exploited in the car-following model to obtain further improvements in safety and comfort by guaranteeing fast response to critical events. In this paper, firstly an Adaptive Model Predictive Control is developed for managing the Cooperative ACC scenario of two vehicles; as a second step, the safety analysis during a cut-in manoeuvre is performed, extending the platooning vehicles number to four. The effectiveness of the proposed methodology is proved in different driving scenarios such as diverse cruising speeds, steep accelerations and aggressive decelerations. Moreover, the controller is validated by considering various speed profiles of the leader vehicle, including a real drive cycle obtained using a random drive cycle generator software. Results show that the proposed control strategy is capable of quickly responding to unexpected manoeuvres and of avoiding collisions between the platooning vehicles, still ensuring a minimum safety distance in the considered driving scenarios.

Relatori: Daniela Anna Misul
Anno accademico: 2020/21
Tipo di pubblicazione: Elettronica
Numero di pagine: 88
Soggetti:
Corso di laurea: Corso di laurea magistrale in Ingegneria Meccanica
Classe di laurea: Nuovo ordinamento > Laurea magistrale > LM-33 - INGEGNERIA MECCANICA
Aziende collaboratrici: Teoresi SPA
URI: http://webthesis.biblio.polito.it/id/eprint/19499
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