A facile physics-based model for non-destructive diagnosis of battery degradation

The identification of battery degradation is of significant importance for estimating the state of health. Loss of lithium inventory (LLI), loss of active materials of the negative electrodes (LAMNE), and loss of active materials of the positive electrodes (LAMPE) are three main degradation modes. This paper proposes an advanced model based on open circuit voltage and differential voltage (DV) fitting to diagnose and quantify the degradation modes of batteries at different stages, showing high fidelity. This physics-based model avoids solving many partial differential equations and is not computationally demanding. Using commercial batteries with NCA/SiC electrodes as a case study, the LLI, LAMPE, and LAMNE induced by battery cycling and storage at various temperatures, State-of-Charge, and charging/discharging rates are systematically identified and analyzed.