MUMBAI, India, Oct. 26 -- Intellectual Property India has published a patent application (202641123355 A) filed by Ms. Emilin Thomas Kangappadan, Christ College Of Engineering, Thrissur, Kerala; Dr Needhu Varghese, Christ College Of Engineering, Thrissur, Kerala; and Mr Jinu K T, Christ College Of Engineering, Thrissur, Kerala on October 15, 2026, for Deep Neural Network And Long Short-Term Memory Based Estimation Of Battery State Of Health And Remaining Useful Life.
Inventors include Ms. Emilin Thomas Kangappadan, Christ College Of Engineering; Dr Needhu Varghese, Christ College Of Engineering, Thrissur, Kerala; and Mr Jinu K T, Christ College Of Engineering, Thrissur, Kerala.
The application for the patent was published on October 23, 2026, under issue no. 43/2026.
Abstract: A system and method for estimating the state of health (SOH) and remaining useful life (RUL) of a lithium-ion battery are described. The measurement subsystem acquires battery operating parameters including voltage and current, and the controller transfers measurement records to computing device for storage and preprocessing. The processed data are supplied to trained machine learning models. A deep neural network estimates SOH, while a long short-term memory model estimates RUL from time-ordered battery features. The workflow supports evaluation of model predictions against reference battery-aging data and can be implemented using embedded data acquisition hardware and a separate computing platform. SOH predicted by deep neural network approach is found to be within the accepted error rate of ±5% and long short time memory neural network model estimates a battery’s RUL effectively with an accuracy of ±10 cycles.
Disclaimer: Curated by HT Syndication.
