The automotive industry, particularly in the high-performance vehicle sector, is increasingly committed to achieving decarbonization through the development of innovative and sustainable powertrains. This thesis investigates one such solution by focusing on fuel cell vehicles and presents a comparative study of two advanced simulation platforms: GT-Suite and Simcenter Amesim. The primary objective is the development of a Battery Electric Vehicle (BEV) model within Simcenter Amesim, validated against data obtained from previous GT-Suite simulations performed by the host company. Once validated, the study extends to the calibration and integration of a Fuel Cell System (FCS) into the BEV architecture, enabling direct comparisons between the two tools. A central focus of this research is the modeling of the cooling system, with particular attention to critical components such as heat exchangers, radiators, and intercoolers, which serve as key elements of comparison between GT-Suite and Amesim. Finally, the study explores the import of 3D CAD piping geometries into the software, with the aim of generating accurate 1D models to improve the fidelity of pressure loss simulations across complete piping networks. This approach allows for a direct comparison on how pressure loss predictions are executed between the two tools.
The automotive industry, particularly in the high-performance vehicle sector, is increasingly committed to achieving decarbonization through the development of innovative and sustainable powertrains. This thesis investigates one such solution by focusing on fuel cell vehicles and presents a comparative study of two advanced simulation platforms: GT-Suite and Simcenter Amesim. The primary objective is the development of a Battery Electric Vehicle (BEV) model within Simcenter Amesim, validated against data obtained from previous GT-Suite simulations performed by the host company. Once validated, the study extends to the calibration and integration of a Fuel Cell System (FCS) into the BEV architecture, enabling direct comparisons between the two tools. A central focus of this research is the modeling of the cooling system, with particular attention to critical components such as heat exchangers, radiators, and intercoolers, which serve as key elements of comparison between GT-Suite and Amesim. Finally, the study explores the import of 3D CAD piping geometries into the software, with the aim of generating accurate 1D models to improve the fidelity of pressure loss simulations across complete piping networks. This approach allows for a direct comparison on how pressure loss predictions are executed between the two tools.
Comparative analysis of Simcenter Amesim and GT-Suite for the simulation of a High-Performance Fuel Cell vehicle
FRANCIA, ALBERTO
2024/2025
Abstract
The automotive industry, particularly in the high-performance vehicle sector, is increasingly committed to achieving decarbonization through the development of innovative and sustainable powertrains. This thesis investigates one such solution by focusing on fuel cell vehicles and presents a comparative study of two advanced simulation platforms: GT-Suite and Simcenter Amesim. The primary objective is the development of a Battery Electric Vehicle (BEV) model within Simcenter Amesim, validated against data obtained from previous GT-Suite simulations performed by the host company. Once validated, the study extends to the calibration and integration of a Fuel Cell System (FCS) into the BEV architecture, enabling direct comparisons between the two tools. A central focus of this research is the modeling of the cooling system, with particular attention to critical components such as heat exchangers, radiators, and intercoolers, which serve as key elements of comparison between GT-Suite and Amesim. Finally, the study explores the import of 3D CAD piping geometries into the software, with the aim of generating accurate 1D models to improve the fidelity of pressure loss simulations across complete piping networks. This approach allows for a direct comparison on how pressure loss predictions are executed between the two tools.| File | Dimensione | Formato | |
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Francia.Alberto.pdf
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https://hdl.handle.net/20.500.14251/4081