This work provides an overview of the mechanics of lithium-ion batteries, both from the aging and diagnostics perspective. Battery diagnostics based on mechanical measurements exploit the strong correlation between electrode lithiation and its deformation, resulting in macroscopic cell deformation. Macroscopic deformation is then a proxy for lithium concentration, enabling estimation of state of charge (SOC) and degradation indicators such as loss of active material and lithium inventory. The results demonstrate that SOC estimation algorithms based on deformation measurements are more robust than voltage-based methods, which are sensitive to temperature and aging, requiring constant updates of the algorithm parameters. Moreover, the health of the battery can be assessed through the differential expansion method even under high-current operation, providing results consistent with the traditional differential voltage method but applicable to real-world industrial applications. Mechanics plays a crucial role also in battery degradation. This work presents the application of POLIDEMO, an advanced battery aging model that explicitly accounts for mechanical degradation phenomena, providing a physics-based framework describing the coupled electrochemical–mechanical aging processes in lithium-ion batteries. It enables the prediction of key degradation indicators, including capacity fade—capturing the characteristic knee-point behavior—and the irreversible battery thickness increase associated with long-term aging. The model is validated with multiple aging datasets, demonstrating that parameters calibrated under a single operating condition can accurately predict degradation across diverse aging scenarios.
Clerici et al. (Thu,) studied this question.