What question did this study set out to answer?

The aim is to develop an intelligent EV charging solution that integrates smart grid technology and machine learning for efficient energy management.

April 23, 2026Open Access

Smart grid integrated wireless EV charging system using machine learning

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Authors

AJA. Vamsi Krishna, G. Amrutha Sri Pradha, P. Dhanunjai, T. Ravi Teja, V. Joshyam

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Implication

This project demonstrates an integrated wireless EV charging system using machine learning, suggesting enhanced efficiency and sustainability in energy use.

Key Points

The aim is to develop an intelligent EV charging solution that integrates smart grid technology and machine learning for efficient energy management.
Developed a wireless EV charging system with smart grid integration.
Utilized machine learning algorithms (Random Forest) for analyzing sensor data related to charging behavior.
Implemented IoT functionalities for real-time data monitoring and cloud integration.
The system successfully predicts charging efficiency and detects abnormalities in real-time.
Continuous monitoring of electrical parameters was achieved with embedded sensors.
Demonstrated ecological benefits by integrating solar-powered charging capabilities.

Cite This Study

A. Vamsi Krishna, G. Amrutha Sri Pradha, P. Dhanunjai, T. Ravi Teja, V. Joshyam (2026) studied this question.

synapsesocial.com/papers/69e9baa885696592c86ecc1c https://doi.org/10.5281/zenodo.19676366

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Implication

This project demonstrates an integrated wireless EV charging system using machine learning, suggesting enhanced efficiency and sustainability in energy use.

Smart grid integrated wireless EV charging system using machine learning

Discussion

Member takes

Implication

Key Points

Cite This Study

Smart grid integrated wireless EV charging system using machine learning

Discussion

Member takes

Implication

Key Points

Cite This Study

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