Electrochemical characterization tools for lithium-ion batteries

Lithium-ion batteries are electrochemical energy storage devices that have enabled the electrification of transportation systems and large-scale grid energy storage. During their operational life cycle, batteries inevitably undergo aging, resulting in a gradual decline in their performance. In this paper, we equip readers with the tools to compute system-level performance metrics across the lifespan of a battery cell. These metrics are extracted from standardized reference performance tests, also known as diagnostic tests, conducted periodically during battery aging experiments. We analyze the diagnostic tests from a publicly available dataset (Pozzato et al. in Data Brief 41:107995, 2022) that consists of the capacity test, high pulse power characterization test, and electrochemical impedance spectroscopy. We provide detailed calculation methodologies and MATLAB (R) scripts required to extract capacity, energy, state-of-charge, state-of-energy, open-circuit voltage, internal resistance, power, incremental capacity, and differential voltage. The MATLAB (R) scripts developed to generate the plots in this paper have been made accessible to the public (Ha et al. in Mendeley Data, V3, 2023). The primary objective of this paper is to provide an accessible guide for undergraduate and graduate students, educators, and researchers interested in characterizing the performance and health metrics of batteries. Such characterizations are critical to the development of battery aging models that can be used to improve cycle life estimation and advance battery management system algorithms.