Mathematical Modeling and Simulation of Electrochemical Dynamics in Next-Generation Energy Storage Systems

Abstract

The transition of the world to renewable energy systems and electrification of transport is providing unprecedented needs on the innovative energy storage systems that are at once high-performing, long-term, and essentially without hazards.  Although lithium-ion batteries have been predominant in the market, next-generation chemistries, including solid-state, lithium-sulfur, and multi-valent-ion batteries, are emerging as a result of their promise of increased energy density and enhanced safety and extended lifespan. However, the type of electrochemical process in these systems is described with severe difficulties with regard to forecasting the functionality and ensuring the reliability of the systems. Its efficiency has rendered the traditional equivalent-circuit models to be unable to transport the nonlinear transport, interfacial kinetics and thermal effects which are very critical to cell behavior in the dynamical conditions. In this work, a complex mathematical modeling / simulation system is created that is sufficient to describe the coupled electrochemical and thermal evolution of the emerging battery systems. The governing equations of charge, mass transport, Butler Volker equations of interfacial reaction and a heat balance equation to represent thermal effects are included in the proposed model. Numerical strategy: Mixed finite element-finite volume (FEM-FVM) using a system of spatially distributed electrolyte concentrations, electrode potential and temperature. The framework allows corrects prediction of key performance indicators such as terminal voltage, state-of-charge (SoC), state-of-health (SoH), capacity fade and thermal stability under real world dynamic loading conditions. The lithium-ion and solid-state chemistries of battery are simulated on a comparative basis and the current profile is performed of the electric vehicle drive cycle and grid-support mode. It has been shown that physics-based modeling can predict the life of the cycles with an uncertainly-better predictive accuracy than the standard equivalent-circuit approaches, and, moreover, can give a more detailed account of the degradation mechanisms, including lithium plating, SEI growth and interfacial resistance. Furthermore, high safety margin of solid-state designs is introduced through the thermal-electrochemical coupling analysis. In general, the research indicates the significance of the application of advanced mathematical modeling and multiphysics modeling as a priceless asset in the design, optimization, and safety deployment of energy storage technologies of the next generation in transportation and grid-scale systems.