MUMBAI, India, Oct. 12 -- Intellectual Property India has published a patent application (202641118744 A) filed by Srm Trp Engineering College on October 05, 2026, for Edge Ai-Based Predictive Energy Management And Battery Health Optimization For Hybrid Residential Microgrids.
Inventors include Kirubalakshmi V; Mohamed Jaseen J; Kaviarasu R; Mohamed Fahim S; and Dr. R. Sathishkumar.
The application for the patent was published on October 09, 2026, under issue no. 41/2026.
Abstract: The present invention relates to an Edge AI-Based Predictive Energy Management and Battery Health Optimization System for Hybrid Residential Microgrids. The system integrates hybrid energy sources, rechargeable battery storage, electrical sensing, environmental sensing, battery monitoring, predictive energy management, and local Edge AI processing into a unified platform. A Raspberry Pi 5 functions as the primary Edge AI processing and energy-management controller. A Voltage Sensor Module, ACS712 Current Sensor, DS18B20 Battery Temperature Sensor, DHT11 Temperature and Humidity Sensor, LDR Module, Battery Management System, and PZEM-004T Smart Energy Meter acquire electrical, battery, environmental, and energy-consumption parameters. The Raspberry Pi 5 processes the acquired information locally to predict future energy availability and residential load demand and to estimate battery State of Charge (SOC) and State of Health (SOH). Based on the predicted energy and load conditions together with battery operating condition, the system determines suitable battery charging, discharging, and energy- management actions. A Charge Controller Module, Relay Module, and DC-DC Buck Converter provide associated power-management functions. An OLED Display, LED Indicators and Buzzer provide local system information and alerts. The proposed invention integrates predictive energy management and battery-health monitoring within a localized Edge AI architecture, thereby supporting efficient energy utilization and improved management of battery operation in hybrid residential microgrids.
Disclaimer: Curated by HT Syndication.
