International Journal of New Developments in Engineering and Society, 2025, 9(1); doi: 10.25236/IJNDES.2025.090105.
Wenzhuang Liu1, Shaohui Han2, Xiaowei Li1, Rui Yan3, Jiarun Cui1, Jiayi Sun4
1Department of Architectural, North China University of Science and Technology, Tangshan, China, 063210
2Department of Metallurgical and Energy Sources, North China University of Science and Technology, Tangshan, China, 063210
3Department of Science, North China University of Science and Technology, Tangshan, China, 063210
4Department of Management, Shandong Second Medical University, Weifang, China, 261000
Faced with the global carbon neutrality goal and environmental pollution problems, new energy vehicles (NEVs) have become a key factor in achieving sustainable development due to their emission reduction and energy-saving characteristics. This study addresses the issue of predicting the growth trend of the NEV market in China by constructing a Pearson correlation analysis model to reveal the strong correlation between government R&D investment and NEV production and sales. The study also uses a multiple linear regression model to quantify the impact of different factors on NEV total sales, and an ARIMA model to forecast the development of the NEV market over the next ten years. The study's findings predict that the NEV market in China will show a stable growth trend from 2023 to 2032, with projected sales reaching 1.437,45 million by 2032. These findings provide important decision support for policymakers and industry stakeholders in strategic planning and resource allocation and have significant practical implications for promoting the healthy development of the new energy vehicle industry and responding to the global carbon neutrality goal.
New Energy Vehicles, Growth Prediction, Pearson Correlation, Multiple Linear Regression, ARIMA Model
Wenzhuang Liu, Shaohui Han, Xiaowei Li, Rui Yan, Jiarun Cui, Jiayi Sun. Research on ARIMA Model and Multiple Linear Regression Model of China's New Energy Vehicle Market Development Forecast Research. International Journal of New Developments in Engineering and Society (2025) Vol.9, Issue 1: 34-41. https://doi.org/10.25236/IJNDES.2025.090105.
[1] Li X, Xiao X, and Guo H. A novel grey Bass extended model considering price factors for the demand forecasting of European new energy vehicles[J]. Neural Computing and Applications, 2022, 14(34): 11521-11537.
[2] Zeng B, Li H, Mao C, et al. Modeling, prediction, and analysis of new energy vehicle sales in China using a variable-structure grey model[J]. Expert systems with applications, 2023, 213: 118879.
[3] Liu L, Liu S, Wu L, et al. Forecasting the development trend of new energy vehicles in China by an optimized fractional discrete grey power model[J]. Journal of Cleaner Production, 2022, 372: 133708.
[4] Rietmann N, Hügler B, Lieven T. Forecasting the trajectory of electric vehicle sales and the consequences for worldwide CO2 emissions[J]. Journal of Cleaner Production, 2020, 261: 121038.
[5] Hu R, Ma W, Lin W, et al. Technology topic identification and trend prediction of new energy vehicle using LDA modeling[J]. Complexity, 2022, 2022(1): 9373911
[6] Long S, Liu Q. Research on New Energy Vehicle Sales Forecast and Product Optimization Based on Data Mining[C]//2021 2nd International Conference on Electronics, Communications and Information Technology (CECIT). IEEE, 2021: 1019-1024.