Rapid Thermal Modeling and Discharge Characterization for Accurate Lithium-ion Battery Core Temperature Estimation

The increasing events of fire and catastrophic failure of lithium-ion batteries (LIBs) due to inaccurate thermal information or improper thermal management based on surface temperature data only, once again indicates the necessity of accurate core temperature information. In view of this, a rapid, more convenient but accurate thermal modeling technique for LIB is introduced in this paper using SIMBA. SIMBA is a powerful new generation power electronics simulation software powered by Python. A second-order electro-thermal model-based core temperature estimation scheme is developed in SIMBA. A wide range of battery test data is used for experimental validation of the model. Further, four standard drive cycle profiles are used to assess the impact of discharge current on the core temperature of LIB. The electro-thermal model allows estimating the core temperature from external measurements including voltage, current, and surface temperature without installing a physical core temperature sensor which is practically challenging. The proposed modeling technique is extremely convenient and the model is computationally efficient and simple enough to be implemented in practical purpose lithium-ion battery management systems.