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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM65585

VoltIQ: Smart EV Charging Station Finder and Range Prediction System

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM65585

Volume:

10 |

6 |

Jun 2026

Pages:

1-7

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM65585

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

Aswathy Kumar K U

Aswathy Kumar K U

Department of Computer Applications

Nehru Institute of Information Technology and Management, Coimbatore, Tamil Nadu, India

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P.Sivakumar

P.Sivakumar

Department of Computer Applications

Nehru Institute of Information Technology and Management, Coimbatore, Tamil Nadu, India

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Abstract

Electric vehicles are becoming more common in India, but many users still find it hard to know how far their vehicle can go before the battery runs out, and they often struggle to find a working charging station nearby. VoltIQ is a web application built to help with these problems. It predicts how far an EV can travel by taking into account the battery level, battery health, weather, temperature, speed, terrain, traffic, and the weight of passengers and luggage. It also helps users find the best charging station near them by ranking stations based on distance, waiting time, available slots, charging speed, and current load. In addition, the application supports trip planning, slot booking, and keeps a record of past charging sessions. An admin panel is provided for managing stations and users. The backend was built using FastAPI and the frontend using Next.js 15 with React 19.

KEYWORDS

Electric Vehicle Range Prediction EV Charging Station Trip Planning FastAPI Next.js Battery Health Station Ranking

Cite This Article

Aswathy Kumar K U, P.Sivakumar, "VoltIQ: Smart EV Charging Station Finder and Range Prediction System," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 6, pp. 1-7, Jun 2026. https://doi.org/10.55041/IJSREM65585

Full Article/Conclusion

This paper described the design and implementation of VoltIQ, a web-based electric vehicle range prediction and charging station management application developed for EV users in India. The application combines a multi-factor range prediction model with station discovery, trip planning, and booking features to support users throughout their journey. The system estimates the available driving range based on battery level, battery health, weather, temperature, speed, terrain, traffic, and passenger load. Additional features such as charging station ranking, trip feasibility checking, slot booking, charging history, and an admin panel for station management provide complete support for everyday EV use. The implementation results show that the application can help users make better decisions about when and where to charge, reducing dependence on fixed manufacturer range values and manual station searches. The developed platform demonstrates how a combination of practical prediction methods and integrated features can improve the EV charging experience for users in growing markets like Tamil Nadu.

References

[1] R. Xiong, J. Cao, and Q. Yu, "Reinforcement Learning-Based Real-Time Energy Management for Hybrid Energy Storage System in the Plug-In Hybrid Electric Vehicle," Applied Energy, vol. 211, pp. 538–548, 2023. [2] T. Fletcher, H. Kim, and A. Forsyth, "Electric Vehicle Range Prediction Using Multi-Factor Environmental and Operational Parameters," IEEE Transactions on Vehicular Technology, vol. 72, no. 3, pp. 2841–2853, 2023. [3] S. Rezaei, M. Abdollahi, and P. Noel, "Battery Health Estimation and Range Prediction for Electric Vehicles Using Data-Driven Methods," Journal of Power Sources, vol. 514, pp. 230–245, 2022. [4] Y. Wang, Z. Chen, and L. Liu, "EV Charging Station Recommendation System Based on Multi-Criteria Decision Making," IEEE Access, vol. 10, pp. 67234–67245, 2022. [5] K. Bhatt and R. Sharma, "Route Planning for Electric Vehicles with Charging Stop Optimization," International Journal of Electric and Hybrid Vehicles, vol. 14, no. 2, pp. 112–127, 2023. [6] FastAPI Documentation, Tiangolo, Available: https://fastapi.tiangolo.com [7] Next.js Documentation, Vercel Inc., Available: https://nextjs.org/docs [8] SQLite Consortium, "SQLite Database Engine Documentation," Available: https://www.sqlite.org [9] OpenStreetMap Contributors, "OSRM: Open Source Routing Machine," Available: https://project-osrm.org [10] OpenWeatherMap, "Weather API Documentation," Available: https://openweatherm

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Publication Date

6/27/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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