Power System Cycle Impact Data Based on Electric Internal Combustion Engines

Nowadays, some companies are turning their attention to Life Cycle Assessment (LCA) of automobiles in order to control energy consumption, reduce production costs, and improve production efficiency. This article intended to take a Chinese brand of pure electric vehicles (EVs) and internal combustion engine vehicles (ICEVs) as the research objects. By comparing the life cycles of the two driving modes, the environmental effect characteristics at different stages of the full life cycle were obtained, and the key factors that have a significant impact on the environment were identified. Given that the main focus of this study is to compare the environmental effects of fuel vehicles and electric vehicles, in addition to the composition of electricity consumption in the Chinese power grid, all relevant data on upstream raw materials and energy production processes were sourced from GaBi. This article intended to supplement the Chinese LCA database by improving it based on it. In the calculation of comprehensive environmental effects, it was assumed that all environmental influencing factors were equal, and the weights of each factor were equal. In the stage of obtaining raw materials, the normalized result of eutrophication was 0.57. In the production and manufacturing stage, the normalization result of acidification was 0.5. This article helped guide designers to optimize design and reduce the impact of vehicles on the environment.

Authors

Institutions

Publication Details

Published
2024-08-14
DOI
https://doi.org/10.1109/peeec63877.2024.00052
Primary Topic
Power Systems and Renewable Energy
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Power System Cycle Impact Data Based on Electric Internal Combustion Engines

Bin Ma, Shan Deng
Power Systems and Renewable Energy
article

Power System Cycle Impact Data Based on Electric Internal Combustion Engines

Bin Ma, Shan Deng
article en

Abstract

Nowadays, some companies are turning their attention to Life Cycle Assessment (LCA) of automobiles in order to control energy consumption, reduce production costs, and improve production efficiency. This article intended to take a Chinese brand of pure electric vehicles (EVs) and internal combustion engine vehicles (ICEVs) as the research objects. By comparing the life cycles of the two driving modes, the environmental effect characteristics at different stages of the full life cycle were obtained, and the key factors that have a significant impact on the environment were identified. Given that the main focus of this study is to compare the environmental effects of fuel vehicles and electric vehicles, in addition to the composition of electricity consumption in the Chinese power grid, all relevant data on upstream raw materials and energy production processes were sourced from GaBi. This article intended to supplement the Chinese LCA database by improving it based on it. In the calculation of comprehensive environmental effects, it was assumed that all environmental influencing factors were equal, and the weights of each factor were equal. In the stage of obtaining raw materials, the normalized result of eutrophication was 0.57. In the production and manufacturing stage, the normalization result of acidification was 0.5. This article helped guide designers to optimize design and reduce the impact of vehicles on the environment.

Jinan Maternity And Care Hospital (CN)
Affordable and clean energy
Openalex Percentile: Top 72%
Power Systems and Renewable Energy
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.