Temporal Sensitivity Analysis for Enhanced Dynamic Equivalent Circuit Modeling of Lithium-ion Batteries in On-board Battery Management Systems

State-of-the-art lithium-ion battery state estimation techniques, including state-of-charge, state-of-health, and remaining useful life in battery management systems (BMS), are extensively dependent on equivalent electric circuit model (ECM) parameters. ECM parameters are subject to change due to battery aging, changes in operating temperature, and other operating conditions. Therefore, updating the model parameters in real-time by on-board BMS is essential to maintain the accuracy of state estimation where ECM is used as the primary building block. ECM parameters obtained in laboratory conditions cannot guarantee accuracy in onboard BMS throughout the entire life cycle of an electric vehicle battery. Currently, onboard state estimation techniques use static ECM parameters due to complexity and computational time in parameterization and online computation, especially with higher-order ECMs. Therefore, this paper presents a comparative analysis of 2-RC, 3-RC, and 4-RC ECMs concerning parameterization time, computational cost, and accuracy, providing an understanding of the possible integration of dynamic ECM models through regular parameterization in onboard BMS. The sensitivity analysis depicts that the 3-RC model would be most appropriate for considerably high accuracy for a BMS with moderate computational power, ensuring safe and reliable state estimation throughout the lifetime of the battery. Moreover, with the changes in ambient conditions, as the sensitivity of R<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> and C<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> are much lower compared to other parameters thus, these do not need update with the changes in operating temperature.