Smart Electric Vehicle Charging Slot Booking and Route Optimization Using Artificial Intelligence

Abstract

The rapid growth of electric vehicles (EVs) has increased the need for charging services that are reliable, predictable, and easy to plan around, particularly during long distance travel. Existing charging applications mainly list nearby stations and rarely combine the battery level of the vehicle, the planned route, charger availability, traffic, and expected waiting time in a single decision. This paper presents the design of an intelligent web-based system for charging slot booking and route optimization that applies artificial intelligence (AI) and machine learning (ML). The user enters a destination and the current battery percentage. The system estimates the remaining driving range, identifies candidate charging stations along the route, predicts availability and waiting time from historical booking and demand data, and ranks the stations with a weighted multifactor score. The driver can then reserve a slot in advance and receive map-based navigation to the selected station. The architecture combines a React front end, a Flask application programming interface, a MySQL database, a scikit-learn recommendation engine, and an open map service. A worked scenario with illustrative values shows how the ranking balances distance, waiting time, availability, and traffic. The proposed approach is expected to reduce waiting at stations, lower range anxiety, and distribute demand more evenly across charging infrastructure.

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