Authors : P. Sridevi; B. Usha Sree; G. Sindhu Pranathi; P.V. Sanjana; Priya Agarwal

Volume/Issue : Volume 11 - 2026, Issue 4 - April

Google Scholar : https://tinyurl.com/5b8uzzf5

Scribd : https://tinyurl.com/4fmzuz8f

DOI : https://doi.org/10.38124/ijisrt/26apr681

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Abstract : Electric vehicles (EVs) are becoming more popular, but many people still worry about limited battery range and finding reliable charging stations. Most navigation systems focus only on finding the shortest route and do not consider whether the battery will last for the entire trip. This can lead to range anxiety and inefficient travel. In this paper, we present a route planning system designed especially for electric vehicles as it considers the vehicle’s battery percentage. This approach checks whether a route is feasible based on the vehicle’s battery level before suggesting it. Energy usage is estimated using travel distance, and charging stations along the route are identified when necessary. The system also uses real-time routing services to generate optimized paths and can adjust the route if the traffic conditions change. Haversine distance computation is used to determine geographic distances when identifying charging stations near the travel route. The system allows users to define a minimum battery reserve percentage that should remain upon reaching the destination. In addition to route planning, the system maintains a database of charging stations and provides a charging slot booking feature that allows EV users to reserve available charging slots in advance. It also lets users create accounts for secure access, sends email confirmations and billing details after booking, and shows routes and charging stations on a map. Users can view their past trips and bookings. The results show that our method improves route reliability and makes better use of available battery power compared to traditional shortest- path navigation systems. The proposed framework is a practical and efficient solution for real-world EV navigation applications.

Keywords : Route Planning, Battery Management, Haversine Distance, Heuristic Algorithm, Charging Stations, Charging Feasibility Search, Charging Slot Booking.

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