Intellectual Property India Publishes Patent Application for Iot-Enabled Intelligent Energy Management And Predictive Control, And Cost Optimization System For Hybrid Electric Vehicles Incorporating Biopolymer-Based Energy Storage Materials

MUMBAI, India, Oct. 26 -- Intellectual Property India has published a patent application (202641122997 A) filed by Dr. Arockia Panimalar S; Dr. J Sivasankari; Sathishkumar A; Dr. M. Sakthivel; Dr. Vijayalakshmi M; M. Karthik; G. Rajadurai.; Dr. G Vijayakumar; Dr. P. D. R. Vijayakumar; and Shaik John Sydulu on October 14, 2026, for Iot-Enabled Intelligent Energy Management And Predictive Control, And Cost Optimization System For Hybrid Electric Vehicles Incorporating Biopolymer-Based Energy Storage Materials.

Inventors include Dr. Arockia Panimalar S; Dr. J Sivasankari; Sathishkumar A; Dr. M. Sakthivel; Dr. Vijayalakshmi M; M. Karthik; G. Rajadurai.; Dr. G Vijayakumar; Dr. P. D. R. Vijayakumar; and Shaik John Sydulu.

The application for the patent was published on October 23, 2026, under issue no. 43/2026.

Abstract: This work proposes an Internet-of-Things (IoT)-enabled energy management and economic model predictive control (MPC) architecture for a parallel hybrid electric vehicle (HEV) with a conventional traction battery and an optional biopolymer-enabled auxiliary energy-storage unit. A vehicle-resident controller fuses powertrain measurements, state-of-charge estimation, short-horizon load prediction, battery-aging proxies, and operating-cost terms. Secure and rate-limited cloud services may provide traffic forecasts and fleet-level model updates without becoming part of the safety-critical control loop. The formulation minimizes fuel consumption, electricity-equivalent usage, degradation penalties, and operating costs under power balance, state-of-charge, power, temperature, and reserve constraints. Candidate cellulose-, chitosan-, and alginate-derived electrolyte systems are discussed as research-stage material options rather than commercially validated traction-battery replacements. A verification protocol, model assumptions, sensitivity analyses, and explicitly hypothetical numerical illustrations are provided. The contribution is a reproducible system-design and experimental-validation roadmap; no quantitative vehicle efficiency improvement is claimed without measured or simulation-generated evidence. Accompanied Drawing [FIG. 1] [FIG. 2] [FIG. 3] [FIG. 4]

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