A recent study has conducted a comprehensive evaluation of low-order equivalent circuit models for lithium-ion batteries, considering both their electrical and thermal behavior. The research focused on how these models represent the internal dynamics of batteries under different loading conditions, including constant current and dynamic load profiles. This type of analysis is crucial for improving the accuracy of battery management systems (BMS), which are fundamental for optimizing the performance, safety, and lifespan of batteries in applications such as electric vehicles and renewable energy storage.

The work addresses the need for battery models that are accurate enough to capture complex phenomena like heating and degradation, yet also computationally efficient for real-time implementation in a BMS. Equivalent circuit models (ECMs) are a popular choice due to their balance between complexity and precision. However, their performance can vary significantly depending on how they are parameterized and the operating conditions. The novelty of this study lies in its focus on joint electro-thermal evaluation, which is essential given that temperature has a direct impact on the internal resistance and capacity of batteries.

The researchers evaluated different ECM configurations, comparing their ability to predict the terminal voltage and internal temperature of battery cells. The results provide guidance on the selection and parameterization of ECMs for specific applications, highlighting the strengths and limitations of each model under realistic load scenarios. This detailed characterization is a step forward in developing more robust and predictive BMS algorithms, which will in turn contribute to greater efficiency and reliability of lithium-ion battery systems.