MUMBAI, India, Aug. 17 -- Intellectual Property India has published a patent application (202641095048 A) filed by Dr. R. Ramkumar; Dr. M. Lakshmi; Dr. N. Vinothini; Dr. V. Buvanesh Pandian; Mrs. M. Sasikala; Mrs. A. Divya; Ms. G. Atchaya; and Mrs. D. Akshayaa on August 05, 2026, for Artificial Intelligence-Based Energy Management And Control Technique For Fuel Cell Electric Vehicles.

Inventors include Dr. R. Ramkumar; Dr. M. Lakshmi; Dr. N. Vinothini; Dr. V. Buvanesh Pandian; Mrs. M. Sasikala; Mrs. A. Divya; Ms. G. Atchaya; and Mrs. D. Akshayaa.

The application for the patent was published on August 14, 2026, under issue no. 33/2026.

Abstract: [062] The present invention relates to an artificial intelligence-based energy management and control technique for fuel cell electric vehicles. The invention provides an intelligent system comprising a fuel cell stack, a rechargeable battery pack, a regenerative braking module, an artificial intelligence prediction engine, an adaptive energy optimization controller, a thermal management module, and a supervisory control unit configured to receive real-time operational data from a plurality of vehicle sensors. The artificial intelligence prediction engine predicts future vehicle power demand, battery operating conditions, hydrogen consumption, thermal loading, and regenerative energy availability using machine learning techniques. Based on the predicted operating conditions, the adaptive energy optimization controller dynamically allocates power between the fuel cell stack and the battery pack, optimizes regenerative braking, and proactively regulates thermal management to improve energy utilization and component reliability. The system continuously updates prediction models using newly acquired operational data to enhance decision-making accuracy throughout the vehicle life cycle. The proposed invention reduces hydrogen consumption, extends driving range, improves fuel cell durability, increases battery lifespan, enhances regenerative energy recovery, minimizes thermal stress, and provides efficient, adaptive, and reliable energy management for fuel cell electric vehicles operating under varying driving and environmental conditions. Accompanied Drawing [FIGS. 1-2]

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