A real-time optimal charging current estimation algorithm for predicting battery temperature in electric vehicles

초록

Temperature-related issues can potentially arise from the increased battery temperature during charging because of the high current. Therefore, to ensure safe battery management, battery current should be controlled to prevent from exceeding the upper-temperature limit. However, considering external factors, such as the changing environment and battery cooling system, to control the temperature presents challenges. In this study, a temperature prediction method with thermal modeling and real-time optimal charging current-estimation algorithm were proposed to modulate the temperature of lithium-ion batteries in electric vehicles (EVs). The proposed modeling method has a simple structure and high accuracy because it experimentally identifies the parameters using a curve-fitting method. However, errors occurred in the battery model when the heat dissipation system was operated using the proposed model. Therefore, an additional thermal model consideration for the heat dissipation system was constructed in the proposed study, and a optimal charging current are predicted in real time using this thermal model that considering heat dissipation system. The validation of the proposed algorithm predicts the optimal charging current that reaches the upper-temperature limit when the heat dissipation system operates based on 175 Ah nickel‑cobalt‑manganese (NCM) battery cells for EVs. Applying the optimal current-estimation algorithm considering temperature, it was verified that the battery temperature remained within 50 °C and estimated a safe optimal charging current with an average temperature error of 0.55 °C. © 2025 Elsevier Ltd

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