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Forecasting new energy vehicle sales using a fractional reverse accumulation non-equidistant grey time power model

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  • Liang, Xuting
  • Wang, Qiong
  • Chen, Wei

Abstract

As global carbon neutrality goals drive the rapid growth of the new energy vehicle industry, accurately forecasting its sales has become a critical challenge. This paper proposes a novel fractional reverse accumulated non-equidistant grey time power model. Using fractional and reverse accumulation operators, the proposed model improves forecasting capability and the ability to capture data trends. Furthermore, its non-isometric operator effectively handles non-equidistant time series data. The model’s effectiveness is validated through simulation experiments and multiple practical case studies. Finally, the model is applied to forecast the annual sales of battery electric vehicles in China. The results predict that China’s annual sales of battery electric vehicles are expected to reach between 8.60 million and 9.10 million units by 2026, providing a comprehensive quantitative analysis for assessing market trends.

Suggested Citation

  • Liang, Xuting & Wang, Qiong & Chen, Wei, 2026. "Forecasting new energy vehicle sales using a fractional reverse accumulation non-equidistant grey time power model," Applied Mathematics and Computation, Elsevier, vol. 519(C).
    • Handle: RePEc:eee:apmaco:v:519:y:2026:i:c:s0096300325006630
    DOI: 10.1016/j.amc.2025.129938
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    References listed on IDEAS

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