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Performance optimization of a lean-burn DI hydrogen engine via numerical simulation

Federico Ferraro

Performance optimization of a lean-burn DI hydrogen engine via numerical simulation.

Rel. Mirko Baratta, Daniela Anna Misul. Politecnico di Torino, Corso di laurea magistrale in Automotive Engineering (Ingegneria Dell'Autoveicolo), 2022

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Abstract:

The project starts from the results of a research project previously carried out by CRF, AVL and POLITO on a DI NG engine. The first phase is concerned with the calibration of 1D predictive simulation models for the reference engine and it is performance-oriented; in the second phase the influence of the change from NG to H2 fuelling is considered, by contemplating1D analysis, with a particular focus on injection, mixing and combustion processes. From the analyses carried out, by keeping a stoichiometric air-fuel ratio for both CNG and hydrogen, an increase of about 2.5% in torque, power and bmep has been recorded. If switching to a lean mixture, in particular with RAFR=2, it has been registered a torque, power and bmep decrease of about 50%, that is improvable by acting on combustion and injection law, as explained and detailed in the core of the project.

Relatori: Mirko Baratta, Daniela Anna Misul
Anno accademico: 2021/22
Tipo di pubblicazione: Elettronica
Numero di pagine: 116
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: NON SPECIFICATO
URI: http://webthesis.biblio.polito.it/id/eprint/23685
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