Plug-in Electric Vehicles Adoption: A Review of Forecasting Methodologies, Policy Impacts, and Future Trajectories in Major Global Markets

Accurate forecasting of Plug-in Electric Vehicle (PEV) market sales share is vital for evidence-based policymaking, yet existing studies employ diverse and often fragmented methodologies, creating a need for systematic review to clarify their analytical foundations and comparative strengths. This study classifies mainstream forecasting methodologies into theory-driven and data-driven approaches, providing a review of five representative models' merits, limitations, and potential directions. Analysis reveals that leading approaches increasingly employ cross-scale model coupling, theory-data fusion, and modular design to harness complementary strengths, improving model robustness and predictive accuracy. Furthermore, the study compares PEV policies and market forecasts in China, the United States, and Europe—the world's three largest automotive markets. The findings indicate a strong linkage between forecast convergence and policy stability. China demonstrates the highest policy consistency and institutional consensus, with an average forecast of 81.3% PEV new vehicle sales share by 2030. Europe's projections average 62.8%, driven by binding emissions mandates, whereas the U.S. exhibits greater uncertainty, averaging 31.1% amid fragmented regulations and uncertain policies. These disparities highlight the decisive role of policy coherence and regulatory predictability in shaping PEV market outlooks.