Forecasting Development Trends and Analysing Influencing Factors of New Energy Electric Vehicles in China: Based on Multi-level Analysis and Time Series Modelling

Authors

  • Zihan Wei

DOI:

https://doi.org/10.54097/1pydn504

Keywords:

Multi-level Analysis; Time Series Model;New Energy Electric Vehicles.

Abstract

This study comprehensively analyses the current development status and future trends of China's new energy electric vehicle industry, and constructs a multilevel analysis model by integrating data from multiple sources, systematically assessing the influence weights of factors such as policy orientation, economic development, technological innovation, infrastructure construction and environmental protection on the development of new energy vehicles. On this basis, ARIMA model, Holt's index smoothing model and multiple linear regression method are used to quantitatively forecast the development of China's new energy electric vehicle market in the next ten years. Meanwhile, this study explores the potential impact of the popularity of new energy vehicles on the global traditional energy vehicle industry pattern, and analyses the effectiveness of domestic and international government support policies. The results of the study show that policy promotion and technological advancement are the key drivers of the rapid growth of China's new energy vehicle market, and it is expected that the penetration of new energy vehicles will continue to profoundly change the ecology of the automotive industry in the next ten years, and exert an important thrust on the transformation of the global energy structure.

References

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Published

08-05-2024

Issue

Section

Articles

How to Cite

Wei, Z. (2024). Forecasting Development Trends and Analysing Influencing Factors of New Energy Electric Vehicles in China: Based on Multi-level Analysis and Time Series Modelling. Mathematical Modeling and Algorithm Application, 2(1), 44-48. https://doi.org/10.54097/1pydn504