Nowadays, the need to focus on clean and eco-sustainable mobility is increasingly felt, also considering the more stringent regulations in favor of the ecological transition. A viable solution that is being consolidated is vehicle hybridization. Among different hybrid technologies, a promising one is the fuel cell hybrid electric vehicle (FCHV), particularly because this solution is based on hydrogen, a resource foreseen in all the future policies about environmental sustainability. However, FCHVs are still not widespread, mainly due to high costs; thus, their performance enhancing and design optimization are strategic goals to be pursued so as to make them more competitive. This paper presents and discusses the optimization of several FCHV design and control parameters, such as fuel cell system power, battery specific energy, power to weight ratio and final battery state of charge target. Hierarchical modeling approach was applied, so as to derive, in a cascading manner, fast model-based tools from a comprehensive FCHV simulator. The resulting procedure allows immediately singling out the best values for each analyzed variable, along with its influence on the fuel economy. The latter point was particularly deepened, by carrying-out model-based sensitivity analyses to accurately quantify, for a known vehicle configuration, the impact of each variable percentage change in terms of fuel economy. More specifically, a map-based method has been proposed to compare paired design and control variables influence on fuel economy to obtain a performance-based ranking of analyzed variables. The results discussion underlines the effectiveness of the proposed tool in providing a solid support in the preliminary design and upgrading tasks (e.g., adaptation to most representative driving habits and/or to specific region-dependent traffic conditions) of FCHV lay-out, especially when aiming at maximizing fuel economy.

Parametric and Sensitivity Analyses to Support Decision Making Tasks in Fuel Cell Hybrid Vehicle Design

Sorrentino M.
2021

Abstract

Nowadays, the need to focus on clean and eco-sustainable mobility is increasingly felt, also considering the more stringent regulations in favor of the ecological transition. A viable solution that is being consolidated is vehicle hybridization. Among different hybrid technologies, a promising one is the fuel cell hybrid electric vehicle (FCHV), particularly because this solution is based on hydrogen, a resource foreseen in all the future policies about environmental sustainability. However, FCHVs are still not widespread, mainly due to high costs; thus, their performance enhancing and design optimization are strategic goals to be pursued so as to make them more competitive. This paper presents and discusses the optimization of several FCHV design and control parameters, such as fuel cell system power, battery specific energy, power to weight ratio and final battery state of charge target. Hierarchical modeling approach was applied, so as to derive, in a cascading manner, fast model-based tools from a comprehensive FCHV simulator. The resulting procedure allows immediately singling out the best values for each analyzed variable, along with its influence on the fuel economy. The latter point was particularly deepened, by carrying-out model-based sensitivity analyses to accurately quantify, for a known vehicle configuration, the impact of each variable percentage change in terms of fuel economy. More specifically, a map-based method has been proposed to compare paired design and control variables influence on fuel economy to obtain a performance-based ranking of analyzed variables. The results discussion underlines the effectiveness of the proposed tool in providing a solid support in the preliminary design and upgrading tasks (e.g., adaptation to most representative driving habits and/or to specific region-dependent traffic conditions) of FCHV lay-out, especially when aiming at maximizing fuel economy.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/4781477
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