Pengaruh Fast Charging pada Baterai LI-Ion Bertipe NMC, LFP, dan LCO dengan PyBaMM: Untuk Optimasi Pencegahan Lithium Plating

Abstract

The growing demand for electric vehicles and portable electronic devices has increased the need for efficient and reliable energy storage systems. Lithium- ion batteries are widely used due to their high energy density and long cycle life. However, fast charging can accelerate battery degradation by inducing lithium plating, a phenomenon in which metallic lithium deposits on the anode surface when the lithium-ion intercalation rate becomes insufficient. The tendency of lithium plating varies among different battery chemistries, including Nickel Manganese Cobalt (NMC), Lithium Iron Phosphate (LFP), and Lithium Cobalt Oxide (LCO), due to their distinct electrochemical characteristics.This study employed the PyBaMM software using the Doyle-Fuller-Newman (DFN) electrochemical model to simulate and analyze lithium plating under fast-charging conditions. Simulations were conducted by varying the operating temperature and charging rate (C-rate) to investigate their effects on anode potential. Model accuracy was evaluated by comparing simulation results with experimental data using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Relative Mean Absolute Error (R-MAE), and Relative Root Mean Square Error (R-RMSE). The results indicate that low temperatures and high charging rates significantly increase the likelihood of lithium plating due to increased electrochemical polarization and reduced lithium-ion diffusion. Model validation demonstrated good agreement between simulation and experimental data, with R-MAE values ranging from 1.469% to 5.348% and R-RMSE values ranging from 1.848% to 7.500%. Lithium plating analysis showed that LCO exhibited the highest plating risk of 28.7% with a minimum anode potential of -0.3902 V, followed by NMC with a risk of 26.5%. In contrast, LFP demonstrated the lowest plating risk of 24.4% and the highest average anode potential of 0.0231 V, indicating superior resistance to lithium plating. These findings suggest that PyBaMM is an effective tool for modeling lithium plating behavior and evaluating battery safety under fast- charging conditions. Furthermore, the results highlight the superior electrochemical stability of LFP compared to NMC and LCO and provide valuable insights for the development of safer and more adaptive fast-charging strategies for lithium-ion batteries.