Identification of the Best Vehicle Segment for e-Taxis from a Life Cycle Assessment Perspective

2022-24-0020

09/16/2022

Features
Event
Conference on Sustainable Mobility
Authors Abstract
Content
In European Union (EU), transport causes about a quarter of the total greenhouse gases (GHG) emissions and road vehicles are the biggest contributors, with nearly three-quarters of the overall GHG emissions. In this context, many governments are adopting different strategies to achieve a sustainable mobility, including the electrification of public transport, such as full electric taxis (e-taxis). Indeed, battery electric vehicles (BEVs) represent a promising solution towards the achievement of sustainability since they involve zero emissions during the use phase, despite indirect emissions are generated during the charging of the traction battery according to the specific national electricity mix. However, a proper choice of the vehicle segment for the e-taxi and its battery capacity can represent a crucial factor in reducing the overall environmental impacts. Indeed, a battery with a higher capacity can reduce the battery aging for the same traveled distance and then the number of battery replacements. The purpose of this research is to identify the best vehicle segment for the e-taxis fleet according to GHG emissions within the vehicle lifespan. To this end, a cradle-to-grave Life Cycle Assessment (LCA) and battery aging simulations for Lithium-ion batteries are conducted, basing on the state-of-art standard for test driving cycles and average emissions of the EU electricity mix. Results show how the battery aging can determine a higher number of battery replacements for smaller vehicles during their lifespan and, thus, higher GHG emissions due to manufacturing e recycling phases of extra batteries. In particular, this is the case when a scenario of 8-years lifespan is considered, with emissions up to 3.7% higher.
Meta TagsDetails
DOI
https://doi.org/10.4271/2022-24-0020
Pages
7
Citation
Silvestri, L., De Santis, M., Mendecka, B., and Bella, G., "Identification of the Best Vehicle Segment for e-Taxis from a Life Cycle Assessment Perspective," SAE Technical Paper 2022-24-0020, 2022, https://doi.org/10.4271/2022-24-0020.
Additional Details
Publisher
Published
Sep 16, 2022
Product Code
2022-24-0020
Content Type
Technical Paper
Language
English