Research on the Development of New Energy Electric Vehicles in China Based on Correlation Analysis and Ridge Regression Models

Abstract

This paper analyses the main factors affecting China's new energy electric vehicles and their influencing factors. Firstly, it is necessary to collect data, construct indicators, analyse the correlation between indicators, then construct a ridge regression model to obtain the correlation coefficient of each indicator, and finally compare the size of the absolute value of the normalised correlation coefficient to analyse the degree of influence of each indicator. It is found that the development of new energy electric vehicles in China is influenced by four areas: policy, technology, economy and market. Eleven factors were selected as sub-indicators, including policy subsidies, number of policies, battery life, energy efficiency ratio, number of patents, GDP per capita, petrol price, average price of new energy electric vehicles, charging cost, industry chain size and number of charging piles. The sales volume as the dependent variable reflects the impact of the development of new energy electric vehicles, the higher the sales volume, the better the development of new energy electric vehicles. Data analysis and modelling were carried out through Spearman correlation analysis, ridge regression model construction and other methods to derive the degree of influence of each indicator on sales volume. The results show that the number of charging piles has the greatest impact on the development of new energy electric vehicles in China, while the energy efficiency ratio has the least impact. The ridge regression model predicts sales better, but performs poorly under special circumstances.