Forecasting battery electric vehicle growth and charging infrastructure needs in Thailand: A macroeconomic and statistical modeling approach - Gomonwattanapanich, Opart; Sivabrovornvatana, Nilubon; Jansa, Pachern (Edelweiss Applied Science and Technology, 2025)
The rapid advancement of electric vehicle (EV) technology over recent years has significantly transformed the global transportation landscape. Many nations have implemented supportive policies aimed at fostering environmental sustainability and decreasing reliance on fossil fuels. Thailand has actively participated in this global shift, experiencing a notable increase in EV imports, heightened consumer interest, and an expanding need for comprehensive infrastructure to facilitate widespread adoption. This study endeavors to project the future number of electric vehicles in Thailand and to estimate the demand for EV charging stations through the application of various statistical models, including the Exponential Curve Projection, Linear Regression, and a predictive model incorporating gross domestic product (GDP) and population metrics. The analysis utilizes historical registration data sourced from the Department of Land Transport, complemented by national GDP and demographic data to develop scenario-based forecasts. Data processing, modeling, and simulation were conducted using advanced tools such as Microsoft Excel and MATLAB. The findings offer valuable insights into short- and medium-term EV growth trajectories and highlight critical infrastructure gaps. These results are intended to support policymakers and industry stakeholders in making informed decisions regarding EV adoption strategies, infrastructure development, and environmental policy formulation in Thailand, thereby promoting sustainable transportation initiatives and economic growth.