MUMBAI, India, Aug. 17 -- Intellectual Property India has published a patent application (202621078212 A) filed by Sage University; Ms. Sakshi Agrawal; Dr. Prashant Jain; Dr. Hemang Shrivastava; Prof. Suranjit Kosta; and Dr. Nidhi Tiwari on June 24, 2026, for A System And Method For Real-Time Battery Health Monitoring In Energy Storage Systems.
Inventors include Ms. Sakshi Agrawal; Dr. Prashant Jain; Dr. Hemang Shrivastava; Prof. Suranjit Kosta; Dr. Nidhi Tiwari; Onkar Singh; Jayesh Patil; Rishabh Raghuvanshi; and Karuna Bhagwan Tayade.
The application for the patent was published on August 14, 2026, under issue no. 33/2026.
Abstract: ABSTRACT A System and Method for Real-Time Battery Health Monitoring in Energy Storage Systems A system and method for real-time battery health monitoring in energy storage systems is disclosed. The system comprises a battery sensing module configured to continuously acquire battery operational parameters including voltage, current, temperature, internal resistance, state-of-charge, cycle count, capacity retention, charging characteristics, and energy throughput from one or more battery cells or battery packs. A battery parameter processing module preprocesses and analyzes the acquired information, while a battery health analytics engine estimates battery state-of-health and evaluates degradation conditions. A degradation prediction module predicts battery aging trends and remaining useful life using artificial intelligence and machine-learning techniques. An anomaly detection module identifies abnormal operating conditions including thermal instability, excessive capacity fade, resistance growth, charging anomalies, and cell imbalance. An alert and recommendation module generates condition-based alerts and predictive maintenance recommendations. A communication module transmits battery-health information, diagnostic reports, and maintenance notifications to monitoring platforms and user devices. The disclosed invention improves battery reliability, operational safety, lifecycle management, maintenance efficiency, and overall energy- storage-system performance through continuous intelligent monitoring and predictive analytics.
Disclaimer: Curated by HT Syndication.
