Mobile Application for EV Charging Station Locator and Real Time Slot Booking

Abstract

EV Charging Station Locator and Slot Booking System is a web-based application developed to provide electric vehicles (EV owners) with an optimized solution for searching nearby charging stations, verifying real-time availability, and charging slot reservations. With the rapid deployment of EVS, the system addresses the need for efficient infrastructure by providing features such as geolocation-based transmitter search, slot availability, and real-time updates for GPS-enabled navigation. The platform improves user convenience by booking EV owners in advance, reducing wait times, and ensuring a problem-free charging experience. Integrating real data with user design ensures an intuitive experience while simultaneously optimizing the use of charging stations. The system not only benefits EV owners, but also supports efficient management of charging infrastructure and contributes to sustainable transport.

Introduction

With the rise of electric vehicles (EVs), there is growing demand for efficient charging networks. This project develops a mobile application designed to simplify the EV charging experience by providing real-time charging station locations, live slot availability, instant reservations, and secure payment integration.

Key Features and Benefits:

• Real-time availability and slot reservations: Users can view available charging slots and book them in advance to reduce waiting times.

• Enhanced GPS-based mapping: Uses Google Maps API for accurate, location-based search of nearby charging stations.

• Secure digital payments: Integrates payment gateways like Razorpay and Stripe for cashless transactions within the app.

• Dual user roles: Supports both EV owners and station operators, with admins able to manage station status and view user activity through a dashboard.

• User-friendly interface: Offers detailed station profiles, pricing, user ratings, and notifications for a smooth user experience.

Motivation:

Traditional methods are insufficient for managing EV charging demand, leading to delays, inefficient energy use, and inconvenience. The app addresses these gaps by providing up-to-date information, minimizing delays, optimizing resource use, and supporting sustainable transportation.

Related Work:

Existing apps like PlugShare and ChargePoint offer station location and availability but lack comprehensive reservation and management features. This project improves upon them by adding real-time slot bookings and an admin dashboard for station operators.

Methodology:

• Requirement analysis identifying needs of EV owners and station operators.

• System design with Flutter frontend, Firebase backend, and real-time Google Maps integration.

• App development focusing on responsive UI, secure user authentication, and seamless data sync.

• Security measures including user authentication, data encryption, and role-based access.

Implementation:

• User registration with secure authentication.

• Location access to detect nearby stations.

• Detailed station info including load types and pricing.

• Real-time slot booking system preventing double bookings.

• Integrated payment gateways for secure cashless transactions.

Experimental Results:

• Successful detection of nearby stations via GPS mapping.

• Real-time updates reflected across users instantly.

• Reliable slot booking and fast payment processing.

• Performance tests showed acceptable response times and high success rates under simulated loads.

Conclusion

The development and investigation of EV charging station locators and real-time slot reservation mobile applications have greatly improved the accessibility and efficiency of EV shops. By integrating real-time slot availability updates and an enhanced reservation system, the app reduces search times, minimizes latency, and improves user-friendly. User feedback highlights user-friendliness and effectiveness in addressing common challenges among EV owners. Additionally, the system benefits charging station operators by optimizing slot utilization and reducing traffic congestion. This innovation contributes to a more sustainable transportation ecosystem that supports a global shift towards clean energy solutions. Future improvements include AI-controlled predictive analytics for demand forecasting and integration in smart grid systems to further improve efficiency.

References

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Copyright

Copyright © 2025 Dharmaraj Patil, Lokesh Borse, Dinesh Bachhav, Rushikesh Sonje, Prathmesh Patil. 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.