Prediction of new energy vehicles ownership with PCA-logistic model under peak carbon dioxide emissions and carbon neutrality

Guoyi Tang, J. Shao, Xinxin Yu, Jianhua Gao
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Abstract

New energy vehicles play a pivotal role in the realization of carbon peak and carbon neutrality. The prediction of the ownership of new energy vehicles is of great significance to realize the goal of environmental protection in transportation field. The fluctuations of new energy vehicle ownership data follow a long-term nonlinear trend influenced by complex impact factors where nonlinear relationships are in between. Therefore, it is important to use reasonable and accurate methods to analyze and forecast the new energy vehicle ownership to facilitate the rational formulation of policies. In order to study the change of vehicle ownership under the influence of multiple factors such as GDP, urbanization rate and highway mileage, the method of combining principal component factor analysis and logistic nonlinear model is adopted. The result shows that the nonlinear logistic regression curve obtained has a higher fitting degree with the actual data. According to the industry planning, the number of new energy vehicles in 2035 is about 156 million.
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二氧化碳排放峰值与碳中和条件下新能源汽车保有量PCA-logistic预测
新能源汽车在实现碳峰值和碳中和方面发挥着举足轻重的作用。新能源汽车保有量的预测对于实现交通运输领域的环保目标具有重要意义。新能源汽车保有量数据波动具有长期的非线性趋势,受复杂影响因素的影响,影响因素之间存在非线性关系。因此,运用合理、准确的方法对新能源汽车保有量进行分析预测,有利于政策的合理制定。为了研究GDP、城镇化率、公路里程等多重因素影响下的机动车保有量变化,采用主成分分析与logistic非线性模型相结合的方法。结果表明,所得到的非线性logistic回归曲线与实际数据有较高的拟合程度。根据行业规划,2035年新能源汽车保有量约为1.56亿辆。
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