M. Ram
Polymaterials App, LLC, Florida, United States
Keywords: Lithium battery, thermal runaway, machine learning
PolyMaterials App, LLC has developed modern technology to manage temperature rise in batteries, particularly lithium (Li) batteries, using supercapacitors (SCs) to prevent thermal runaway in energy storage systems. This approach is based on a novel idea (PCT/US21/47454) developed by Principal Investigator, Dr. Ram. The method integrates a relatively small supercapacitor and a smart controller as a supplementary system to provide additional power to the load when the battery temperature rises. A unique feature of this system is the use of a machine learning (ML) algorithm to control the charging and discharging cycles of the supercapacitor, ensuring an energy-efficient and significantly safer solution. Our experiments and simulations have demonstrated that managing the charge-discharge cycles of the main battery and the backup storage can effectively reduce overall temperature over extended energy storage periods. We have successfully developed both software and hardware for charging and discharging 12V batteries without thermal runaway. A prototype feasibility study has been completed for a 12V battery system, and under this opportunity, we plan to extend the operating range to significantly higher voltages (48V - 400V). We are collecting data in more realistic scenarios, which is used for training of the ML algorithm that controls the thermal runaway.