Car makers are subject to a strong regulatory pressure to make the industry more environmentally sustainable. In this context, many research and industrial activities have been concentrated in the field of sustainability through the development of innovative materials, manufacturing technologies and production processes. This paper presents a tailored framework for estimating the potential of lightweighting to mitigate the Global Warming Potential (GWP) impact within the automotive sector. The framework is based on the Life Cycle Assessment (LCA) modelling of the use stage, and it is able to evaluate the effects of lightweight solutions in the application to a wide range of cars, both in terms of propulsion technologies (Internal Combustion Engine Vehicles, ICEVs, and Battery Electric Vehicles, BEVs) and vehicle segments. In addition, the assessment framework can estimate the effect of different electricity grid mixes when modelling the production of energy consumed by BEVs. The added value of the method is the ability to estimate the use stage GWP through indicators which are ready-to-use in any practical case study: starting from the knowledge of component mass only, the operation phase is easily and immediately assessed, thus limiting the inventory modelling to the sole production and End-of-Life (EoL) steps. This way, the work of the LCA analyst is greatly facilitated, with notable savings in terms of time and personnel effort. The framework is validated through the application to a practical case study from literature, which deals with different lightweight measures in the application to a series of automotive components. Results highlight the potentiality of the method to perform a detailed Life-Cycle (LC) analysis, as well as the ability to identify the most profitable application fields of innovative solutions.

Tailored Framework to Analyze and Interpret LCA’s Results in Automotive Lightweighting / Francesco Del Pero, Andrea Antonacci, Massimo Delogu. - In: SAE TECHNICAL PAPER. - ISSN 0148-7191. - ELETTRONICO. - (2022), pp. 0-0. [10.4271/2022-37-0029]

Tailored Framework to Analyze and Interpret LCA’s Results in Automotive Lightweighting

Francesco Del Pero;Andrea Antonacci;Massimo Delogu
2022

Abstract

Car makers are subject to a strong regulatory pressure to make the industry more environmentally sustainable. In this context, many research and industrial activities have been concentrated in the field of sustainability through the development of innovative materials, manufacturing technologies and production processes. This paper presents a tailored framework for estimating the potential of lightweighting to mitigate the Global Warming Potential (GWP) impact within the automotive sector. The framework is based on the Life Cycle Assessment (LCA) modelling of the use stage, and it is able to evaluate the effects of lightweight solutions in the application to a wide range of cars, both in terms of propulsion technologies (Internal Combustion Engine Vehicles, ICEVs, and Battery Electric Vehicles, BEVs) and vehicle segments. In addition, the assessment framework can estimate the effect of different electricity grid mixes when modelling the production of energy consumed by BEVs. The added value of the method is the ability to estimate the use stage GWP through indicators which are ready-to-use in any practical case study: starting from the knowledge of component mass only, the operation phase is easily and immediately assessed, thus limiting the inventory modelling to the sole production and End-of-Life (EoL) steps. This way, the work of the LCA analyst is greatly facilitated, with notable savings in terms of time and personnel effort. The framework is validated through the application to a practical case study from literature, which deals with different lightweight measures in the application to a series of automotive components. Results highlight the potentiality of the method to perform a detailed Life-Cycle (LC) analysis, as well as the ability to identify the most profitable application fields of innovative solutions.
2022
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0
Francesco Del Pero, Andrea Antonacci, Massimo Delogu
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1282483
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