Recent Progress in the Physics-Constrained State of Health Estimation for Lithium-Ion Batteries

Due to the high energy density and long cycle life, lithium-ion batteries play an important role in electric transportation and energy storage systems. Therefore, accurate state of health (SOH) estimation is of great significance for battery lifetime management and safe operation. Existing SOH estimation methods are highly dependent on data and suffer from insufficient physical interpretability and limited cross-scenario generalization. To address the issues, introducing physical information constraints enables physical consistency requirements to be incorporated into the estimation process and confines the estimation to the physically feasible domain, thereby improving prediction performance and enhancing physical interpretability. From the perspective of sources of physical constraints and forms of constraint implementation, the review systematically summarizes the current research. Regarding the sources of constraints, equivalent circuit constraints, mechanism-based constraints, and degradation-dynamics constraints are introduced, and the advantages, disadvantages, and applicable scenarios of typical implementation forms, including physics-informed loss, physics-informed initialization, physics-driven architecture design, and virtual physics-driven fusion, are summarized. Finally, current challenges and future research directions are outlined based on a comprehensive comparison of existing studies, with the aim of providing a useful reference for future research on physics-informed SOH estimation.