RII Track-4:NSF: Enable Next-Generation Solid-State Batteries via Dynamic Modeling and Control: Theory and Experiments

University Of Oklahoma Norman Campus, Norman OK

Investigators

Abstract

This project aims to advance the state-of-the-art in energy storage systems by promoting the understanding of emerging solid-state battery (SSB) to realize improved safety and performance via dynamic modeling, control, and experiments. Current Lithium-ion battery (LIB) has exhibited serious safety vulnerabilities and propensity to failure during overcharging, thermal excursions, and mechanical abuses. Meanwhile, electrification of power-critical sectors such as aviation, long-haul trucks, and electric vehicles also promote a quest for pushing the battery performance envelope towards even higher energy density. The SSB can produce significant improvements in energy and power capability thanks to the replacement of the liquid electrolyte used in LIB by a solid-state counterpart. The success of this project constitutes crucial steps forward to unleash the full potentials of SSB to achieve enhanced thermal stability, increased energy density, and faster charging capability. The development of reliable SSB can substantially enhance the energy and power capability of electrochemical energy storage systems while reducing costs, thus enables a faster dissemination of electrified transportation and accelerates the transition towards an environmentally sustainable economy in the United States. This Research Infrastructure Improvement Track-4 EPSCoR Research Fellows project would provide a fellowship to an Assistant Professor and training for a graduate student at Oak Ridge National Laboratory. The project envisions a transformative scheme that fuses the benefits of battery material properties and dynamic control, highlighted by three scientific contributions. First, a holistic multiphysics model that enables investigations of functional connections across different length and time scales in SSB systems. Besides providing design guidance, multiphysics models offer rich information for optimal control that safely steers the system trajectory while still delivering on key performance metrics. Second, these multiphysical models, however, are governed by partial differential equations (PDEs) in which nonlinearity, parametric uncertainty, and safety constraints present formidable control-theoretic challenges. This research will advance nonlinear control theory of uncertain and nonlinear parabolic PDE systems to reveal the full electrochemical potentials of SSB and will serve as a tool with which one can perform safety-constraint-aware control. Third, a comprehensive experimental validation will be conducted, including hardware-in-the-loop experiments and post-mortem material characterization. The objective is to uncover the extent to which the multiphysics model-based control improves the safety and performance of energy-dense SSB. The key to this endeavor is a close collaboration with ORNL who provides advanced computational technologies for high-dimensional multiphysics modeling and the state-of-the-art battery material characterization facilities to discover SSB degradation patterns using a broad range of electron microscopies. Multiple new techniques will be cultivated within this project - each can manifest self-sufficient research directions with tremendous impact on future energy storage innovations. 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.