Impedance response simulation strategies for lithium-ion battery models

Abstract

The battery is an electrochemical system which may be considered a black box with no practical way of observing processes occurring within in a nondestructive manner at an affordable cost. Fortunately, most physical and chemical processes in electrochemical systems can be distinguished by their distinct characteristic time constants. Electrochemical impedance spectroscopy (EIS) is a powerful technique to distinguish internal processes within batteries based on their frequency response. EIS has been successful at identifying relevant electrochemical mechanisms and battery parameters and therefore can be integrated with model-based battery management systems (BMS) which are critical for improving the battery life and performance. In this article, we provide our perspective on different simulation strategies for modeling the impedance response of lithium-ion batteries, implementation of EIS models in BMS, and some challenges associated with achieving a computationally efficient approach. • EIS is a powerful technique to characterize and identify internal processes within batteries based on their frequency response. • Battery models for EIS can largely be categorized into Empirical and Physics-based models. • Reduced order physics-based models (SPM,P2D) are proven to be faster, accurate with higher fidelity. • Battery management systems (BMS) integrated with EIS can prove to a good diagnostic tool for batteries in operation. • Robust and efficient state/parameter estimation techniques are critical for BMS implementation.