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Investigation of the Potential of Hydrogen to improve the Powertrain Efficiency using 1D-CFD Software

Oliviero Agnelli

Investigation of the Potential of Hydrogen to improve the Powertrain Efficiency using 1D-CFD Software.

Rel. Federico Millo. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Meccanica, 2021

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The continuous tightening of emissions limits is pushing the automotive world towards "green" alternatives to fossil fuels. In this context, hydrogen is a promising solution for the future of mobility, both with Fuel Cell vehicles and hydrogen internal combustion engines. The goal of the work is to design a hydrogen powertrain that meets the requirements of: High Performances, High Efficiency and zero emissions without after-treatment systems. In a first phase, after a detailed analysis of the different solutions, the hydrogen internal combustion engine has been selected as the most promising solution to meet both emissions and performance targets. Therefore a V8 turbocharged gasoline engine, currently used on a production car, has been converted into an hydrogen version capable to provide the same performances with negligible emissions. Consequently, through the use of a 1D-CFD software, an hydrogen engine concept with 600HP and high efficiency with almost zero NOx emissions, has been designed. In order to correctly reproduce the behavior of the engine under different loads and speeds, different new methodologies to take into account the hydrogen properties have been developed, like the one to predict the hydrogen knock occurrence. This last one has been developed using 0D-CFD chemistry simulations and it has been validated against experimental results. Then, after a complete redesign of the existing supercharging system using innovative technologies such as eTurbo and Back-to-Back compressors, full load and part load conditions were simulated. The resulting engine maps were then used in a vehicle model to perform driving cycle simulations in order to calculate NOx emissions and fuel consumption data. In conclusion, the engine and vehicle data were fed into the simulator to run lap time simulations at the Nürburgring and analyze the telemetry data.

Relators: Federico Millo
Academic year: 2020/21
Publication type: Electronic
Number of Pages: 91
Corso di laurea: Corso di laurea magistrale in Ingegneria Meccanica
Classe di laurea: New organization > Master science > LM-33 - MECHANICAL ENGINEERING
Aziende collaboratrici: PORSCHE Engineering Services GmbH
URI: http://webthesis.biblio.polito.it/id/eprint/19579
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