Predicting the Market Penetration Rate of China’s Electric Vehicles Based on a Grey Buffer Operator Approach

Qingfeng Wang (), Xiaohui Liu and Limin Wang
Additional contact information
Qingfeng Wang: Systems and Industrial Engineering Technology Research Center, Zhongyuan University of Technology, Zhengzhou 450007, China
Xiaohui Liu: School of Economics and Management, Zhongyuan University of Technology, Zhengzhou 450007, China
Limin Wang: Systems and Industrial Engineering Technology Research Center, Zhongyuan University of Technology, Zhengzhou 450007, China

Sustainability, 2023, vol. 15, issue 19, 1-13

Abstract: On the decision of whether to continue to implement the industrial support policy, two scenarios are set to predict the market penetration rate of China’s electric vehicles (EVs) (In this paper, the term Electric Vehicles (EVs) refers to both full-battery EVs and plug-in hybrids). In order to weaken the disturbance caused by international oil prices and industrial policies, the grey buffer operator was firstly applied, to preprocess the original data series. The sales data for EVs and fuel vehicles were buffered for second order and first order, respectively. Based on the obtained buffer data sequence, the GM (1, 1) model was used to predict the sales of EVs and fuel vehicles between 2022 and 2025 in China. The results demonstrate a significantly improved fit compared to directly modeling the raw data. This method is suitable for studying the market penetration rate prediction of China’s EVs. If the industry support policies continue (Scenario I), an EV market penetration rate of 22.45% can be achieved in 2024, and the expected target can be achieved one year ahead of schedule. Even if the corresponding industrial support policies are no longer implemented (Scenario II), the EV market penetration rate will reach 20.58% in 2025, and the set target of 20% will be achieved on schedule.

Keywords: electric vehicles (EVs); market penetration rate; grey prediction; grey buffer operator (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/19/14602/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/19/14602/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:19:p:14602-:d:1255777

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().