Lithium-ion (Li-Ion) batteries are commonly used in electric vehicles (EVs) and consumer electronics because they have higher energy and power density and better durability than lead-acid and nickel-metal hydride batteries. However, their operating temperature significantly influences Li-Ion batteries' performance.

Therefore, it is essential to study battery performance across different ambient temperatures. Accurate battery temperature prediction requires a detailed analysis of heat generation, including joule heat and reaction heat, which are influenced by ambient temperature and the battery's state of charge (SoC). These factors must be considered for accurate performance assessment.

Numerical modeling has emerged as a more effective approach for capturing heat generation in batteries. Electrochemical models (ECMs) have gained popularity among various types of numerical models due to their balance of accuracy, ease of parametrization and implementation. They have been widely used for real-time battery management applications, including battery parameter prediction.

Based on physical principles, ECMs can accurately calculate heat generation, including joule heat and reaction heat, with clear interpretations. SoC and temperature, both of which influence the parameters of the ECM, have been successfully integrated into these models. This paper investigates the effects of SoC, discharge current and ambient temperature on the ECM parameters.