Pietro Iurilli


Last Name

Iurilli

First Name

Pietro

ORCID

0000-0003-2484-805X

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2021 - 20225
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Publications 1 - 5 of 5
  • EIS applied to Li-Ion Batteries: Modelling Cell Aging for Comprehensive SoH Estimation
    Item type: Doctoral Thesis
    Iurilli, Pietro (2022)
  • Detection of Lithium-Ion Cells' Degradation through Deconvolution of Electrochemical Impedance Spectroscopy with Distribution of Relaxation Time
    Item type: Journal Article
    Iurilli, Pietro; Brivio, Claudio; Wood, Vanessa (2022)
    Energy Technology
    Herein, a methodology to investigate aging of commercial cylindrical Li-ion cells is introduced. Distribution of relaxation time (DRT) method is applied to deconvolute electrochemical impedance spectroscopy (EIS) measurements and separate those polarization effects that are usually overlapped in the frequency domain by means of a peak-based representation. Half-cells are built at the beginning and end of life to link the electrochemical and aging processes occurring at anode and/or the cathode sides. Moreover, lab-made full-cells are exploited to verify the reproducibility when compared with cylindrical cells. The results of an extensive analysis of around 500 EIS spectra return an unambiguous attribution of different electrochemical processes to different time constants and ultimately to different DRT peaks. Digital imaging validates graphite degradation, mainly related to lithium plating. Scanning electron microscopy validates the degradation at NMC cathode, mainly attributed to particle cracking. It is concluded that DRT peaks allow to characterize cell aging and their tracking can help to develop more reliable state of health estimators.
  • EIS2MOD: A DRT-Based Modeling Framework for Li-Ion Cells
    Item type: Journal Article
    Iurilli, Pietro; Brivio, Claudio; Carrillo, Rafael Eduardo; et al. (2022)
    IEEE Transactions on Industry Applications
    The correct assessment of battery states is essential to maximize battery pack performances while ensuring reliable and safe operation. This work introduces EIS2MOD, a novel modelling framework for Li-ion cells based on Distribution of Relaxation Time (DRT). A physically based Electric Circuit Model (ECM) is developed starting from Electrochemical Impedance Spectroscopy (EIS) and Open Circuit Voltage (OCV) measurements. DRT is applied to deconvolve the electrochemical phenomena from the EIS. The presented methodology is based on: i) DRT calculation from EIS, ii) DRT analysis for ECM configuration and iii) Model parameters extraction and fitting. The proposed framework is applied to large format Li-ion pouch cells, which are tested over the whole State of Charge (SoC) range and a wide temperature range (-10C to 35C). Different current profiles have been tested to validate the model, showing its high accuracy in reproducing the battery cell behavior (e.g. RMSE on the battery terminals voltage lower than 1.50% for driving cycle simulations at variable temperature and SoC). An additional advantage of EIS2MOD is its light computational load thus offering an attractive framework for battery management system implementation.
  • On the use of electrochemical impedance spectroscopy to characterize and model the aging phenomena of lithium-ion batteries: a critical review
    Item type: Review Article
    Iurilli, Pietro; Brivio, Claudio; Wood, Vanessa (2021)
    Journal of Power Sources
    Electrochemical Impedance Spectroscopy (EIS) is a powerful non-invasive technique used to characterize Lithium-ion cells. Its application allows to identify and track the evolutions of cell degradation processes within a short testing time. This review collects all the available works which have used EIS spectra either to characterize Li-ion cell degradation or to develop Electric Circuit Models (ECMs). The objectives of this work are: (i) to highlight the influence of different aging test conditions on the EIS spectra; (ii) to find the correlations between EIS spectra variations and the underlying degradation mechanisms and (iii) to list the available options to formulate ECMs from EIS spectra of aged cells. After an exhaustive analysis of the state-of-the-art, a critical review is presented to discuss the existing links between degradation mechanisms and the most reliable solutions to model them.
  • Physics-Based SoH Estimation for Li-Ion Cells
    Item type: Journal Article
    Iurilli, Pietro; Brivio, Claudio; Carrillo, Rafael E.; et al. (2022)
    Batteries
    Accurate state of health (SoH) estimation is crucial to optimize the lifetime of Li-ion cells while ensuring safety during operations. This work introduces a methodology to track Li-ion cells degradation and estimate SoH based on electrochemical impedance spectroscopy (EIS) measurements. Distribution of relaxation times (DRT) were exploited to derive indicators linked to the so-called degradation modes (DMs), which group the different aging mechanisms. The combination of these indicators was used to model the aging progression over the whole lifetime (both in the “pre-knee” and “after-knee” regions), enabling a physics-based SoH estimation. The methodology was applied to commercial cylindrical cells (NMC811|Graphite SiOx). The results showed that loss of lithium inventory (LLI) is the main driving factor for cell degradation, followed by loss of cathode active material (LAMC). SoH estimation was achievable with a mean absolute error lower than 0.75% for SoH values higher than 85% and lower than 3.70% SoH values between 85% and 80% (end of life). The analyses of the results will allow for guidelines to be defined to replicate the presented methodology, characterize new Li-ion cell types, and perform onboard SoH estimation in battery management system (BMS) solutions.
Publications 1 - 5 of 5