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A Comparative Life Cycle Assessment of an Electric, a Hybrid, and an Internal Combustion Engine Vehicle Using Monte Carlo Simulation

Publication Type : Conference Paper

Publisher : Springer Nature Singapore

Source : Lecture Notes in Mechanical Engineering

Url : https://doi.org/10.1007/978-981-19-3467-4_22

Campus : Coimbatore

School : School of Engineering

Department : Mechanical Engineering

Year : 2023

Abstract : Automotive industries spend significant amount of time and effort in designing a vehicle. Thus, it is ensured that the vehicle, throughout its entire life cycle meets or exceeds the environmental requirements. Consumer demand for a sophisticated yet powerful vehicle has been an impediment in achieving a “green vehicle”. Life cycle assessment (LCA) could be an effective tool to the industry in evaluation of the potential options to strike a balance between meeting consumer demands and improving greenness of a vehicle. The objective of the study is to compare environmental impacts of three kinds of vehicles: electric vehicle (EV), hybrid vehicle (HV), and internal combustion engine vehicle (ICEV) over the course of their life. Each vehicle is assessed for its emissions across different impact categories. This is done using the OpenLCA software. As a part of this study, we also develop a model to demonstrate the usefulness of Monte Carlo Simulation (MCS) in LCA. The uncertainty in the input variables is calculated using Monte Carlo Simulation. The findings from the three scenarios (EV, HV, and ICEV) indicate that the comparison between the vehicles depends on the impact category considered. The results also suggest that Monte Carlo Simulation can provide a comprehensive understanding of complex comparisons such as those between EVs, ICEVs, and HVs.

Cite this Research Publication : Sricharan Dwijesh Kurada, Mirza Imtiaz Ali, J. Gokulachandran, A Comparative Life Cycle Assessment of an Electric, a Hybrid, and an Internal Combustion Engine Vehicle Using Monte Carlo Simulation, Lecture Notes in Mechanical Engineering, Springer Nature Singapore, 2022, https://doi.org/10.1007/978-981-19-3467-4_22

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