Multiscale Modelling Methodologies of Lithium-Ion Battery Aging: A Review of Most Recent Developments

Abstract

Lithium-ion batteries (LIBs) are leading the energy storage market. Significant efforts are being made to widely adopt LIBs due to their inherent performance benefits and reduced environmental impact for transportation electrification. However, achieving this widespread adoption still requires overcoming critical technological constraints impacting battery aging and safety. Battery aging, an inevitable consequence of battery function, might lead to premature performance losses and exacerbated safety concerns if effective thermo-electrical battery management strategies are not implemented. Battery aging effects must be better understood and mitigated, leveraging the predictive power of aging modelling methods. This review paper presents a comprehensive overview of the most recent aging modelling methods. Furthermore, a multiscale approach is adopted, reviewing these methods at the particle, cell, and battery pack scales, along with corresponding opportunities for future research in LIB aging modelling across these scales. Battery testing strategies are also reviewed to illustrate how current numerical aging models are validated, thereby providing a holistic aging modelling strategy. Finally, this paper proposes a combined multiphysics- and data-based modelling framework to achieve accurate and computationally efficient LIB aging simulations.