Synergistic Integration of Digital Twins and Data Analysis for Enhanced Operational Efficiency

As global temperatures continue to rise, achieving carbon peaking and carbon neutrality has become a key goal worldwide. New energy electric vehicles (NEEVs), with their low energy consumption, adjustable peak electricity use, and eco-friendly characteristics, are vital for reaching these sustainability targets. Accurately predicting the NEEV market is essential, as it informs strategic decisions and policies that support the swift adoption of clean technologies. Reliable market forecasts drive investment, optimize infrastructure, and ultimately accelerate progress toward a low-carbon future. The system constructed in this study, using data analysis and digital twin methods, effectively improves the accuracy of predicting the future market for new energy vehicles, achieving a precision rate of 96%, which fully demonstrates the advantages of combining these two approaches.