MUMBAI, India, Oct. 26 -- Intellectual Property India has published a patent application (202631123855 A) filed by Dr. Bidrohi Bhattacharjee; Dr. Ankur Ganguly; Dr. Arijit Chakrabarti; Dr. Indraneel Mukhopadhyay; Dr. Dipanwita Sadhukhan; Dr, Goutam Kumar Das; and Mr. Niladri Dutta on October 15, 2026, for A Degradation-Aware Machine Learning Digital Twin For Predictive Energy Management Of Fuel Cell Battery Super Capacitor Electric Vehicles.
Inventors include Dr. Bidrohi Bhattacharjee; Dr. Ankur Ganguly; Dr. Arijit Chakrabarti; Dr. Indraneel Mukhopadhyay; Dr. Dipanwita Sadhukhan; Dr, Goutam Kumar Das; and Mr. Niladri Dutta.
The application for the patent was published on October 23, 2026, under issue no. 43/2026.
Abstract: The present invention relates to a degradation-aware machine learning digital twin for predictive energy management of fuel cell–battery–supercapacitor electric vehicles. The invention provides an intelligent energy management framework configured to monitor vehicle operating parameters, power demand, energy storage conditions, and degradation characteristics of a fuel cell, a battery, and a supercapacitor. The digital twin establishes a virtual representation of the hybrid energy system by integrating real-time operational data with machine learning-based prediction and analysis models. The framework estimates component health and degradation trends, predicts future vehicle power requirements, and determines an optimized power distribution strategy among the fuel cell, battery, and supercapacitor. Based on the predicted operating conditions and degradation states, the system dynamically regulates power allocation to improve energy utilization, reduce excessive component loading, and mitigate degradation of the energy sources. The invention further facilitates adaptive energy management under varying driving conditions, thereby enhancing the operational efficiency, durability, and reliability of fuel cell–battery–supercapacitor electric vehicles.
Disclaimer: Curated by HT Syndication.
