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Lithium-ion batteries show a complex thermo-electrochemical performance and aging behavior. This paper presents a modeling and simulation framework that is able to describe both multi-scale heat and mass transport and complex electrochemical reaction mechanisms. The transport model is based on a 1D + 1D + 1D (pseudo-3D or P3D) multi-scale approach for intra-particle lithium diffusion, electrode-pair mass and charge transport, and cell-level heat transport, coupled via boundary conditions and homogenization approaches. The electrochemistry model is based on the use of the open-source chemical kinetics code CANTERA, allowing flexible multi-phase electrochemistry to describe both main and side reactions such as SEI formation. A model of gas-phase pressure buildup inside the cell upon aging is added. We parameterize the model to reflect the performance and aging behavior of a lithium iron phosphate (LiFePO4, LFP)/graphite (LiC6) 26650 battery cell. Performance (0.1–10 C discharge/charge at 25, 40 and 60°C) and calendaric aging experimental data (500 days at 30°C and 45°C and different SOC) from literature can be successfully reproduced. The predicted internal cell states (concentrations, potential, temperature, pressure, internal resistances) are shown and discussed. The model is able to capture the nonlinear feedback between performance, aging, and temperature.
We present an electrochemical model of a lithium iron phosphate/graphite (LFP/C6) cell that includes combined aging mechanisms: (i) Electrochemical formation of the solid electrolyte interphase (SEI) at the anode, leading to loss of lithium inventory, (ii) breaking of the SEI due to volume changes of the graphite particles, causing accelerated SEI growth, and (iii) loss of active material due to of loss percolation of the liquid electrolyte resulting from electrode dry-out. The latter requires the introduction of an activity-saturation relationship. A time-upscaling methodology is developed that allows to simulate large time spans (thousands of operating hours). The combined modeling and simulation framework is able to predict calendaric and cyclic aging up to the end of life of the battery cells. The aging parameters are adjusted to match literature calendaric and cyclic aging experiments, resulting in quantitative agreement of simulated nonlinear capacity loss with experimental data. The model predicts and provides an interpretation for the dependence of capacity loss on temperature, cycling depth, and average SOC. The introduction of a percolation threshold in the activity-saturation relationship allows to capture the strong nonlinearity of aging toward end of life (“sudden death”).
In this article the high-temperature behavior of a cylindrical lithium iron phosphate/graphite lithium-ion cell is investigated numerically and experimentally by means of differential scanning calorimetry (DSC), accelerating rate calorimetry (ARC), and external short circuit test (ESC). For the simulations a multi-physics multi-scale (1D+1D+1D) model is used. Assuming a two-step electro-/thermochemical SEI formation mechanism, the model is able to qualitatively reproduce experimental data at temperatures up to approx. 200 °C. Model assumptions and parameters could be evaluated via comparison to experimental results, where the three types of experiments (DSC, ARC, ESC) show complementary sensitivities towards model parameters. The results underline that elevated-temperature experiments can be used to identify parameters of the multi-physics model, which then can be used to understand and interpret high-temperature behavior. The resulting model is able to describe nominal charge/discharge operation behavior, long-term calendaric aging behavior, and short-term high-temperature behavior during extreme events, demonstrating the descriptive and predictive capabilities of physicochemical models.