Development of New Prediction Model for Thermal–Electrical Characteristics of Lithium-Ion Batteries Including Low-Temperature Conditions

The development of an accurate and robust analytical model for battery thermal–electrical characteristics is crucial to ensuring stable and reliable operation. In this context, this study proposes a new prediction model that estimates the thermal–electrical characteristics of a lithium (Li)-ion battery with high accuracy and low computational cost. Unlike existing models, the proposed thermal–electrical model (TEM) accurately predicts temperature and voltage for both static and dynamic cycles across a wide range of temperature conditions, requiring fewer initial parameters and equations. The proposed model demonstrated its ability to accurately predict the battery temperature under static discharge conditions with maximum errors of 0.8 and 1.6 K for batteries at 0 and −20°C, respectively. Additionally, it predicted battery voltage with an accuracy of 0.054 and 0.088 V for the two dynamic driving cycles of New European Driving Cycle (NEDC) and US06, respectively, with a maximum error of 0.054 V. Furthermore, the proposed model successfully predicted the battery temperature and voltage during driving cycle at −10°C. It was further extended to predict the battery temperature of a 4S1P module unit with an accuracy of up to 1.8 K, thereby demonstrating that it can replace existing models, even at the module level.