Applied and Computational Engineering

- The Open Access Proceedings Series for Conferences


Proceedings of the 6th International Conference on Computing and Data Science

Series Vol. 64 , 15 May 2024


Open Access | Article

Multi-dimensional analysis of the impact of new energy vehicles on the urban ecological environment and prediction of future trends

Xuanran Tang 1 , Tianbing Yang 2 , Chen Zhang 3 , Zhenglin Xiong 4 , Ruiqi Zhu * 5
1 College of Modern Economics & Management JXUFE
2 College of Modern Economics & Management JXUFE
3 College of Modern Economics & Management JXUFE
4 College of Modern Economics & Management JXUFE
5 Jiangxi University of Software Professional Technology

* Author to whom correspondence should be addressed.

Applied and Computational Engineering, Vol. 64, 30-35
Published 15 May 2024. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Xuanran Tang, Tianbing Yang, Chen Zhang, Zhenglin Xiong, Ruiqi Zhu. Multi-dimensional analysis of the impact of new energy vehicles on the urban ecological environment and prediction of future trends. ACE (2024) Vol. 64: 30-35. DOI: 10.54254/2755-2721/64/20241363.

Abstract

This study examines the development indicators of China's new energy vehicle industry using clustering and multiple regression methods. The indicators are divided into internal and external aspects: external factors, such as the degree of completeness of charging facilities, market demand, policies and regulations, and internal factors, mainly brand types and power costs. By comparing the forecasting models of its industry data, including the exponential smoothing model, grey forecasting model and Brownian forecasting model. The forecast results show that this industry in China maintains a positive development trend in the next ten years. It shows that the development prospect of electric vehicles is very bright.The population competition model is used to model the competitive situation between new energy and traditional energy vehicles, and it is concluded that new energy vehicles are replacing traditional fuel vehicles and promoting the transformation of the automotive industry to be environmentally friendly and efficient.Collect the key measures and points in time that countries have taken to target the development of this industry in China. Analysing the data on the development of the industry before and after these events, it is found that external factors, such as other countries' policies, may inhibit the industry's growth. If other countries take action to thwart this industry in China, it may temporarily break its growth or even lead to a short-term industry recession.

Keywords

New Energy Vehicle Industry, Forecasting Models, Population Competition Models, Carbon Emissions and Ecological Footprint, Environmental Protection and Emission Reduction

References

1. Smith, J., & Liu, H. (2015). "The rise of electric vehicles: Environmental implications and economic analysis." Energy Policy, 45, 634-641.

2. Patel, R., & Sharma, S. (2016). "Charging infrastructure for electric vehicles and its impact on grid stability." Energy Solutions, 4(3), 345-359.

3. Chen, X., & Lin, Z. (2015). "Competition between new and traditional energy vehicles: Battery cost and policy implications." Energy Economics, 52, S53-S62.

4. Lee, A., & Cheng, T. (2019). "Consumer attitudes towards electric vehicles: A review." Transportation Research, 66, 599-613.

5. Patel, R., & Sharma, S. (2016). "Charging infrastructure for electric vehicles and its impact on grid stability." Energy Solutions, 4(3), 345-359.

6. Wang, Y., Zhang, C., & Kim, D. (2018). "Market dynamics and policy efficiencies in electric vehicle adoption." Renewable and Sustainable Energy Reviews, 92, 815-828.

7. Zhao, L., & Wu, Z. (2020). "Predictive models for electric vehicle sales growth: An international perspective." Journal of Global Mobility, 8(1), 77-95.

8. Kumar, A., & Rahman, S. (2018). "Grey system theory approach for forecasting electric vehicle adoption." Technological Forecasting and Social Change, 126, 160-170.

9. Chen, X., & Lin, Z. (2015). "Competition between new and traditional energy vehicles: Battery cost and policy implications." Energy Economics, 52, S53-S62.

10. Greene, D.L., & Park, S. (2014). "The potential role of hydrogen in energy systems with low environmental impacts." Hydrogen Energy, 39(16), 8482-8493.

Data Availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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Volume Title
Proceedings of the 6th International Conference on Computing and Data Science
ISBN (Print)
978-1-83558-425-5
ISBN (Online)
978-1-83558-426-2
Published Date
15 May 2024
Series
Applied and Computational Engineering
ISSN (Print)
2755-2721
ISSN (Online)
2755-273X
DOI
10.54254/2755-2721/64/20241363
Copyright
15 May 2024
Open Access
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Copyright © 2023 EWA Publishing. Unless Otherwise Stated