Abstract: With China's vigorous implementation of the two-carbon policy, the automotive industry is transitioning from traditional to alternative energy sources. Accurate forecasting of new energy vehicle sales can provide statistical support for policy planning. This paper proposed a grey Lotka-Volterra model based on an HP filter to forecast new energy vehicle sales trends. The proposed model overcomes the limitations of the original model in forecasting cyclical data and improves its applicability in small sample data systems. And the competitive forecasting model allows us to explore the market competition or cooperation between various vehicle types. Compared to the two existing models, the new model performs better in forecasting vehicle sales. The study further applies the LCA method to assess the scale of energy consumption and GHG emissions in the automotive sector. The prediction and evaluation results show that new energy vehicle sales will surpass traditional fuel vehicles by 2035 and dominate the vehicle market before 2050. Unfortunately, vehicle electrification has not significantly reduced the transportation industry's environmental concerns. To fully utilize the potential for energy-savings and emission-reduction of new energy vehicles, it is urgent to pursue technological advancements in battery production and power-generating structure. 

Key words: New Energy Vehicle, Grey Lotka-Volterra Model, HP Filter, Sales Forecasting, Environmental Impact