Forecasting the development trend of new energy vehicles in China by an optimized fractional discrete grey power model

Abstract

As an effective technology to reduce traffic pollution emissions, the new energy vehicle industry has developed rapidly in recent years, and the sales of new energy vehicles have doubled in 2021. Accurately forecasting methods provide important references for industrial policy deployment, infrastructure construction and energy demand estimation. In order to predict the development trend of China's new energy vehicle industry under the limited data samples, this paper proposes an optimized discrete grey power model to fit the nonlinear relationship between grey information factor and temporal factor. Firstly, the grey differential equation and its discrete form are directly constructed by using power accumulated data, which simplifies the integral solution process of the traditional grey power model. Secondly, fractional accumulation operator is introduced into the discrete model to ensure the new information priority of the original data. Then, the heuristic algorithm is used to accurately estimate the new parameters of the proposed model. Thirdly, the proposed discrete model is the unified form of two existing discrete grey power models, which expands the scope of modeling and has higher adaptability. Simulation experiments and two numerical cases are used to verify the effectiveness of the proposed method. Finally, the proposed method is used to predict the annual sales and ownership of new energy vehicles in China. The predicted results show that by 2025, China's new energy vehicle sales will reach 8.84 million, accounting for about 24% of the total vehicle sales, surpassing the industry development target (20%) set by the Chinese government.