In this study, commercial 64.6 Ah automotive pouch-cell lithium-ion batteries were used to identify lithium plating (LP) by operando nondestructive electrochemical methods. These methods rely on the analysis of the cell voltage and cell current data, which is usually acquired by a battery management system (BMS). The cells were cycled under specific cycle-rate and temperature boundary conditions (BCs) in order to induce LP. The selected BCs were 0, 10, and 22 °C as test temperatures in combination with 1, 1.5, 2, and 3 C as C-rates. The chosen electrochemical methods are voltage relaxation profile (VRP), differential voltage analysis (DVA), and incremental capacity analysis (ICA). These methods are applied to different sections of charge/discharge cycle voltage and current data to identify the LP. ICA can be applied to the constant current phase of the charge cycle, VRP can be applied during the relaxation time after the charge cycle has finished, and DVA can be applied to the CC-phase of the discharge cycle. These methods are promising, as they do not require additional equipment for data acquisition, proving feasible for online monitoring by the BMS in an electric vehicle. Our investigation shows that in the case of VRP time derivative analysis, with decreasing temperature and increasing C-rate, the plateau/peak position shifts to the right, indicating increased LP during the charge cycle. During the DVA, the characteristic Li-stripping peak shifted to higher capacity values at lower temperatures and higher C-rates. Surprisingly, at a test temperature of 0 °C, the LP is higher at a rate of 2 C than at a rate of 3 C. This effect is attributed to the higher cell polarization at 3 C than at 2 C during the charge phase. In the ICA, at cycling rates of 1.5 C and above, an additional peak was observed at cell voltages above 4 V. This new peak represents an additional reaction taking place at the anode surface, identified as LP. For 0.5 C, no LP was identified in ICA, and LP was only identified at 0 °C at 1 C, whereas LP was always identified at cycling rates of 2 and 3 C at all test temperatures. The described methods and findings open the path toward advanced online LP identification and eventually state-of-health diagnosis of automotive batteries.

This study uses electrochemical impedance spectroscopy (EIS) to investigate coupled effects of mechanical deformation depth and size on impedance responses of large-format prismatic lithium-ion batteries (LIBs). Stepwise out-of-plane deformations were applied using hemispherical impactors of two different diameters (30 mm and 180 mm), representing localized and global mechanical loading while maintaining consistent contact conditions. Cells were deformed to 25%, 50%, 75%, and 95% of the internal short-circuit deformation depth, with EIS measurements conducted at each level. Relative changes of measured impedance parameters and fitted equivalent circuit model (ECM) parameters were analyzed. Results show that localized deformation decreases charge transfer resistance ΔR₁ up to 8.0% and total impedance ΔZ up to 1.6%, indicating enhanced charge mobility due to internal structural damage. In contrast, global compression increases ohmic resistance ΔR₀ up to 2.1% and ΔZ up to 2.0%, likely due to reduced separator porosity. Phase angle ΔPhase showed opposite trends under localized and global loading, reflecting different capacitive responses. These results reveal that deformation depth and size significantly influence EIS measurements, with non-linear interactions and transition points indicative of irreversible damage. These results support the use of EIS as a non-destructive diagnostic tool for identifying mechanical damage in LIBs.

Thermally induced damage in lithium-ion batteries (LIBs) is a critical safety concern, especially when approaching thermal runaway (TR) conditions. In this study, electrochemical impedance spectroscopy (EIS) was used to detect thermally induced damage in large-format prismatic LIBs under sub-critical TR conditions. Thermal abuse tests were first conducted to determine the TR trigger temperature of the investigated cells. A sub-critical target temperature of 170 °C was then selected below the TR trigger temperature for the subsequent thermal load tests. EIS measurements were performed at a constant reference temperature to isolate damage-related impedance changes from temperature effects. Structural changes were analyzed using X-ray computed tomography (CT) and an established temperature estimation method was applied to estimate the cell’s internal temperature. Thermal exposure to 170 °C resulted in reproducible impedance increases, particularly in the low- to mid-frequency region, indicating degradation of transport and interfacial processes. In contrast, elevated temperature caused a pronounced impedance decrease, highlighting the importance of separating temperature effects from damage-related changes. CT analysis revealed significant cell expansion and internal gap formation, providing evidence of structural changes consistent with thermally induced gas generation, which may contribute to the observed electrochemical changes. The combined results demonstrate that temperature-controlled EIS can detect impedance changes associated with thermally induced structural changes under the investigated conditions prior to the TR. The findings highlight the potential of temperature-controlled EIS as a non-destructive diagnostic approach for future battery safety monitoring and early-warning applications.

Lithium-ion batteries (LIBs) in electric vehicle battery packs are assembled under mechanical constraints that exert compression force during operation. During operation, battery cells undergo volumetric changes that cause thickness variations, known as battery swelling. The resulting swelling behavior under mechanical constraints generates force fluctuation. The prediction for force magnitude is critical, as insufficient force compromises electrical contact and structural stability, while excessive force accelerates structural degradation and increases safety risks. However, force sensors have not been widely implemented due to high costs, integration complexity, and reliability concerns, which limits the practical application of force prediction. In this study, we present a coupled electrochemical–mechanical model for predicting compression forces aligning with battery swelling behavior without requiring real-time force sensors during operation. The model predicts the evolution of compression force at an initial external pressure of 0.201 MPa, achieving a mean absolute percentage error (MAPE) of 4.48% during 1C discharge and 7.02% under multi-phase driving cycle conditions, compared with experimental results. The developed framework addresses the existing gap in predicting compression force for mechanically constrained LIBs. The proposed modeling approach enables real-time force monitoring in battery modules, thereby enhancing safety assessment capabilities through force predictions and optimizations.