Multiphysics modeling of lithium-ion, lead-acid, and vanadium redox flow batteries

Abstract

Abstract The increasing demand for batteries’ application in grid-balancing, electric vehicles, and portable electronics has prompted research efforts on improving their performance and safety features. The improvement of batteries involves the comparison of multiple battery designs and the determination of electrochemical and thermal property distributions at the continuum scale. This is achieved by using multiphysics modeling for investigatory battery research, as conventional experimental approaches would be costly and impractical. The fundamental electrochemical models for these batteries have been established, hence, new models are being developed for specific applications, such as thermal runaway and battery degradation in lithium-ion batteries, gas evolution in lead-acid batteries, and vanadium crossover in vanadium redox flow batteries. The inclusion of new concepts in multiphysics modeling, however, necessitates the consideration of phenomena beyond the continuum scale. This work presents a comprehensive review on the multiphysics models of lithium-ion, lead-acid, and vanadium redox flow batteries. The electrochemical models of these chemistries are discussed along with their physical interpretations and common applications. Modifications of these multiphysics models for adaptation and matching to end applications are outlined. Lastly, we comment on the direction of future work with regards to the interaction of multiphysics modeling with modeling techniques in other length and time scales. Molecular-scale models such as density functional theory and kinetic Monte Carlo can be used to create new multiphysics models and predict transport property correlations from first principles. Nanostructures and pore-level geometries can be optimized and integrated into continuum-scale models. The reduction of multiphysics models via machine learning, mathematical simplification, or regression enables their application in battery management systems and energy systems modeling.