MUMBAI, India, Aug. 31 -- Intellectual Property India has published a patent application (202641100070 A) filed by Pokkunuri Pardha Saradhi; G. Jaswanth Varma; D. Sai Prudhvi Raja; K. Venkata Ratnam; and Koneru Lakshmaiah Education Foundation on August 19, 2026, for Artificial Intelligence In Electric Vehicles: A Comprehensive Framework To Enhance Safety, Efficiency, And User Experience.
Inventors include G. Jaswanth Varma; D. Sai Prudhvi Raja; K. Venkata Ratnam; and P. Pardhasaradhi.
The application for the patent was published on August 28, 2026, under issue no. 35/2026.
Abstract: The rapid adoption of Electric Vehicles (EVs) has accelerated the demand for intelligent systems capable of improving vehicle efficiency, safety, reliability, and user experience. Conventional electric vehicle management systems primarily rely on rule-based control mechanisms, which are often limited in handling dynamic driving conditions, battery degradation, energy optimization, and predictive maintenance. To address these challenges, this work proposes a comprehensive Artificial Intelligence (AI)-driven framework that integrates Battery Management System (BMS), Predictive Maintenance, Energy Optimization, Advanced Driver Assistance Systems (ADAS), and intelligent decision-making into a unified architecture. The proposed framework utilizes Machine Learning (ML), Deep Learning (DL), and Reinforcement Learning (RL) algorithms to analyse real-time sensor data, estimate battery parameters such as State of Charge (SOC), State of Health (SOH), and Remaining Useful Life (RUL), optimize energy consumption, predict component failures, and enhance vehicle safety through adaptive decision-making. Furthermore, the framework incorporates a continuous learning mechanism that enables the AI models to improve prediction accuracy and system performance over time. The proposed architecture offers improved battery utilization, enhanced driving range, reduced maintenance costs, increased operational reliability, and a better overall user experience. The modular and scalable design also makes the framework suitable for integration into next-generation intelligent electric vehicles and smart transportation systems.
Disclaimer: Curated by HT Syndication.
