Enhanced Porous Electrode Theory Based Electrochemical Model for Higher Fidelity Modelling and Deciphering of the EIS Spectra

• DOI: 10.1149/1945-7111/ad6eb9
• Publication Date: 2024-08-13T22:54:30Z
• Authors: Igor Mele; Klemen Zelič; Marko Firm; Jože Moškon; Miran Gaberšček; Tomaž Katrašnik
• Keywords: Li-ion battery modelling; deciphering EIS spectra; 0211 other engineering and technologies; Li-ionske baterije, elektrokemijski model, elektrokemijska impedančna spektroskopija, NMC, interpretirati EIS spekter; info:eu-repo/classification/udc/621.35; 02 engineering and technology; elektrokemijska impedančna spektroskopija; interpretirati EIS spekter; electrochemical impedance spectroscopy; Li-ionske baterije; electrochemical model; Li-ion battery modelling, electrochemical model, electrochemical impedance spectroscopy, NMC, deciphering EIS spectra; elektrokemijski model; info:eu-repo/classification/udc/621.35/.36; NMC

Electrochemical impedance spectroscopy (EIS) is essential for non-invasive battery characterization. This paper addresses the challenge of adequate interpretation EIS spectra, which are often complicated by overlapping internal phenomena occurring on similar time scales. We present, first time, a high-fidelity numerical time-domain electrochemical model that can virtually replicate experimental spectra with three superimposed high-frequency semicircles, transition to diffusion tail at elevated imaginary values, and tilted low frequencies. These advanced features were made possible extending state-of-the-art porous electrode innovative sub-models double layer phenomenon carbon black/electrolyte metal Li-anode/electrolyte interfaces, transport charged species through solid electrolyte interphase Li-anode interface. Additionally, we modelled inclination introducing representative active particles varying sizes. Results from custom-made half-cells confirm model’s ability decipher more accurately compared existing models. Moreover, physics-based capable modelling intra-cell reveal states physical parameters batteries using measured spectra. The model, therefore, also enables functionality an virtual sensor, important diagnostics feature in next-generation management systems.