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Related Experiment Video

Updated: Jan 13, 2026

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Smart battery management in EVs using IoT, blockchain, and machine learning.

D Kavitha¹, B Sharmila²

¹Department of Electrical and Electronics Engineering, Sri Ramakrishna Engineering College, Coimbatore, India. kavithaduraiswamy@gmail.com.

Scientific Reports

|October 29, 2025

Summary

This summary is machine-generated.

This study introduces an enhanced Battery Management System (BMS) for electric vehicles (EVs) by integrating the Internet of Things (IoT) and blockchain technology. The new system accurately detects nearby charging stations and ensures secure transactions, improving EV efficiency.

Keywords:

Blockchain Electric vehicles GWO HE IoT Machine learning XGBoost

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Area of Science:

Electrical Engineering
Computer Science
Sustainable Energy

Background:

Electric Vehicles (EVs) face challenges with limited battery range and charging infrastructure availability.
The Battery Management System (BMS) is crucial for EV battery performance, efficiency, and lifespan.
Integrating Internet of Things (IoT) and Blockchain (BC) offers potential for enhanced EV battery management and secure transactions.

Purpose of the Study:

To develop an advanced BMS model for EVs utilizing IoT, blockchain, and machine learning (ML).
To improve energy efficiency and battery state evaluation in EVs.
To ensure secure data storage and financial transactions between EV users and charging stations.

Main Methods:

IoT sensors collected EV data (charge level, distance, location).
Extreme Gradient Boosting (XGBoost) classified charging costs.
Grey Wolf Optimization (GWO) determined optimal charging station location, time, and space.
A permissioned blockchain with homomorphic encryption (HE) secured data and transactions.

Main Results:

The developed BMS model achieved a 97.36% accuracy rate in detecting nearby charging stations.
The system maintained a communication overhead of 35 ms, a 14% improvement over existing models.
Secure and tamper-proof data storage and transaction processing were ensured.

Conclusions:

The integration of IoT, blockchain, and ML significantly enhances EV BMS functionality.
The proposed model addresses key challenges in EV charging accessibility and security.
This approach offers a scalable and secure solution for future electric mobility.