AI + Graphene Based Self-Charging Battery System for EVs and Gadgets
Abstract
The rapid growth of electric vehicles (EVs) and portable electronic devices has increased the demand for high- performance, energy-efficient, and sustainable battery technologies. Conventional lithium-ion batteries suffer from limitations such as long charging time, limited lifespan, thermal instability, and environmental concerns. This paper presents an AI-integrated graphene-based self-charging battery system designed for electric vehicles and electronic gadgets. Graphene, with its exceptional electrical conductivity, high surface area, and thermal stability, enhances battery charging speed, energy density, and lifespan. Artificial Intelligence (AI) is incorporated for smart energy management, predictive monitoring, and optimized charging–discharging cycles. The proposed system also integrates renewable energy harvesting mechanisms such as solar energy to enable self-charging capability. Hardware implementation using microcontrollers, sensors, and IoT modules demonstrates real-time monitoring, safety, and automation. Experimental results indicate improved efficiency, reduced charging dependency, and enhanced system reliability compared to conventional battery systems. The proposed model offers a promising solution for next-generation energy storage with applications in EVs, consumer electronics, and renewable energy systems.
Fields of Study & Subjects
Advanced Battery Technologies Research
Innovative Energy Harvesting Technologies
Electric Vehicles and Infrastructure
Publication details
- Journal / source
- International Journal of Innovative Science and Research Technology (IJISRT)
- Pages
- 87–87
- Publication date
- 7 January 2026