Abstract:

The majority of global road transportation emissions come from passenger and freight vehicles. Electric vehicles (EVs) offer sustainable transportation, but customer concerns about charging services impact adoption rates. Effective infrastructure planning, charge scheduling, pricing, and routing strategies can alleviate perceived risks. Machine learning algorithms, such as forecasting, clustering, and reinforcement-based models, are increasingly used to solve these problems.This study reviews the studies that apply machine learning models to improve EV charging service operations and provides future research directions.