Charge EV: EV Station Locator Web Application

Abstract

The rapid growth of Electric Vehicles (EVs) is transforming the transportation sector globally. However, one of the primary concerns among EV users is locating reliable and available charging stations efficiently. This paper presents ChargeEV, a web-based Electric Vehicle charging station locator application designed to provide real-time, location-based services using GPS and mapping technologies. The system integrates frontend web technologies, backend server architecture, and a structured database to deliver accurate information regarding station availability, charging types, operational hours, and distance calculation. The proposed solution aims to reduce range anxiety, improve infrastructure utilization, and promote sustainable mobility. The system is scalable, cost-effective, and accessible through standard web browsers without requiring dedicated mobile applications.

Introduction

The transportation sector is a major contributor to greenhouse gas emissions, prompting countries like India to promote electric vehicle (EV) adoption through subsidies and infrastructure development. Despite the growing number of EVs and charging stations, users often struggle to locate nearby charging facilities during travel, leading to range anxiety—the fear of running out of battery before reaching a charging point.

To address this issue, ChargeEV is proposed as a browser-based web application that helps users automatically detect their location, find nearby charging stations, check real-time availability, calculate distances, and view charging types (Fast/Normal/AC/DC). The system aims to enhance user convenience and support smart city initiatives.

The literature survey highlights existing EV charging networks such as Tesla Supercharger, ChargePoint, and PlugShare, but notes limitations such as brand-specific platforms, mandatory mobile apps, lack of real-time availability updates, and restricted API access. A centralized, web-based platform like ChargeEV can improve accessibility and scalability.

The identified problems include lack of centralized information, outdated data, no real-time distance calculation, limited cross-platform access, and poor user interfaces. ChargeEV addresses these through a three-layer architecture:

• Presentation Layer: HTML, CSS, JavaScript with responsive UI and map integration.

• Application Layer: Node.js or Python Flask backend with REST APIs and location processing.

• Data Layer: MySQL or MongoDB storing station details, availability, and contact information.
  Google Maps API is used for mapping and navigation.

The system development process includes requirement analysis, system design, implementation (using browser Geolocation API and Haversine formula for distance calculation), testing, and cloud deployment.

Applications include urban commuters, highway travelers, fleet management, government EV monitoring, and smart city systems. Future enhancements include slot booking, payment integration, AI-based demand prediction, IoT charger integration, mobile app development, and government portal integration.

Overall, ChargeEV provides a scalable, user-friendly, real-time solution to improve EV charging accessibility and reduce range anxiety.

Conclusion

Charge EV provides an efficient, scalable, and user-friendly solution for locating EV charging stations using web technologies. By combining GPS tracking, database management, and map visualization, the system improves user confidence and encourages EV adoption. The proposed solution can be further enhanced using AI, IoT, and cloud computing technologies to build a complete smart EV ecosystem.

References

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Copyright

Copyright © 2026 Samiksha Balu Bhand, Sejal Sandip Junnare, Sneha Nilesh Chatur, Samiksha Narayan Dukare, Vishaka Hande. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.