STTR Phase I: Novel State of Health Measurements Through Advanced Lithium-ion Battery Modeling for Secure and Scalable 2nd-Life Battery Deployment

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is the accelerated adoption of electrification and other next-generation technologies, like renewable energy. This project proposes a technology to effectively manage end-of-life lithium-ion batteries through reuse. Enabling these batteries to be safely incorporated into a circular/reuse economy is essential for society to meet the goals of sustainability and net-zero carbon emissions. Extracting further value from post-consumer batteries through reuse provides an economic incentive for original equipment manufacturers to responsibly decommission up to 100% of their retired battery units, thereby foregoing the need to dispose of the battery and manufacture a new one in its place. The proposed technology’s ability to create a practical and safe battery reuse market will not only create a net-negative carbon footprint for the batteries but will also alleviate the stresses currently faced within the lithium (Li)-ion supply chain and bring forward Li-ion technology at more affordable prices. Additionally, the detailed state of health analysis performed by the technology will allow for more informed decision-making in regard to second-life battery allocation, enabling energy storage project managers to lower upfront investment on energy storage, without sacrificing on safety and performance. This STTR Phase I project proposes to develop a novel approach to attain rapid and accurate state of health determinations for second-life lithium-ion batteries. The bespoke technology will utilize novel battery modeling and data analytics to establish an understanding of battery health beyond capacity degradation. The technology’s ability to capture the ensemble effect of numerous battery degradation mechanisms is a significant and needed advance over the incumbent state of the art in battery health analysis. As increased rates of degradation in specific cell parameters would lead to unique performance and operating limitations within the battery, it is imperative to take these parameters into consideration with a state of health assessment, or there is a risk of fatal operating event occurrences such as thermal runaway. This project’s objectives include the development of the rigorous electrochemical model to model the highly complex capacity fading mechanisms within Li-ion batteries, and the development of an algorithm-based state of health estimator that will utilize real-time data and project remaining useful life estimates for second use applications. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.