The study examined the impact of app notifications, including loyalty points, reserved parking, and social norm messages, on driving behavior among 703 EV drivers in the Netherlands.

In this paper, the authors develop a novel AI-assisted power management methodology for fast-charging EV hubs with battery storage systems.

In this study, the authors propose a model predictive control of charging and discharging for EV batteries shared by multiple EMSs based on a mixed-integer quadratic programming method and a quadratic programming method.

The paper introduces Dual Digital Twin, a digital twin with two communication levels, enabling real-time monitoring and control of battery systems in electric vehicles.

The present research combines the traditional COVRP with the emerging EVRP, presenting a novel mathematical formulation that distinguishes between owned and rented vehicles, leading to different solutions depending on the transportation demand.

The study investigates the impact of power ratings on the performance of electric vehicle motors in determining its maximum power output with higher ratings.

This paper proposes and evaluates a strategy that integrates a Time-of-Use (TOU) tariff with Vehicle-to-Home (V2H) operation to promote EV adoption without requiring subsidies or significant investments in grid infrastructure.

The main focus of these studies is to find the important reason that influences preferences.

This study aims to address this gap and advance the understanding of trade-offs among resources, the environment, and the economy, thereby contributing to informed scientific decisions in this domain.

This study addresses the significant and understudied question of how EHVs’ adoption influences CO2 emissions using panel U.S. state-level data over the 2016-2019 period and fixed effects.