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Fuel cell vehicle simulation and optimization based on ADVISOR

Jianyang Lin

Fuel cell vehicle simulation and optimization based on ADVISOR.

Rel. Andrea Tonoli, Angelo Bonfitto. Politecnico di Torino, Corso di laurea magistrale in Automotive Engineering (Ingegneria Dell'Autoveicolo), 2021

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Abstract:

Fuel cell vehicles regain their momentum and become the hot topic of hybrid electric vehicle research with the increasingly severe environmental issues and the maturity of relating technologies. The thesis works aim to investigate the possibility of extending the FCV's driving range by improving the efficiency of the fuel cell and the electric machine based on ADVISOR. The thesis works can be divided into three stages: in the first stage, several control strategies were proposed, including power follower control, discretization method, fuzzy logic control. These proposed control strategies were compared with the power follower control strategy in ADVISOR. The simulations were run over three drive cycles with SUV parameters loaded. The simulated SUV is powered by two energy source, which are a fuel cell modeled by KTH and a Lithium-ion battery. In the second stage, with the goal of increasing the efficiency of the electric machine, a two-speed gearbox was introduced to the driveline. Gear ratio pair and shifting strategy were selected. The impact of the two-speed gearbox on fuel economy was studied. In the third stage, we developed a fuzzy logic controller with driving intention prediction and applied it to the SUV propelled by Toyota Mirai fuel cell system.

Relatori: Andrea Tonoli, Angelo Bonfitto
Anno accademico: 2020/21
Tipo di pubblicazione: Elettronica
Numero di pagine: 83
Soggetti:
Corso di laurea: Corso di laurea magistrale in Automotive Engineering (Ingegneria Dell'Autoveicolo)
Classe di laurea: Nuovo ordinamento > Laurea magistrale > LM-33 - INGEGNERIA MECCANICA
Aziende collaboratrici: Politecnico di Torino
URI: http://webthesis.biblio.polito.it/id/eprint/18858
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