Fast and reliable calibration of thermal-physical model of lithium-ion battery: a sensitivity-based method

Rabissi, Claudio; Sordi, Gabriele; Innocenti, Alessandro; Casalegno, Andrea

doi:10.1016/j.est.2022.106435

Cited by 9 publications

(7 citation statements)

References 64 publications

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“…This setup is employed in all the measurements required for model parameter identification and reliability validation. Details on the testbench are provided in publication [16].…”

Section: Experimental Testbenchmentioning

confidence: 99%

“…For a detailed description of the equations of the DFN and thermal model, we refer the reader to [15,16]. EIS is simulated in the time domain and then converted into a frequency domain by way of fast Fourier transform, as discussed in [15,16]. Optimization of EIS simulation has been performed as detailed in Section 4.2.…”

Section: Physical Modelmentioning

confidence: 99%

“…• usually reproduce discharge curves with satisfactory accuracy; however, to provide physical consistency when simulating LIB operation and dynamics, the reliability should be challenged using EIS, as recently pointed out by several research groups [16,17]. The simulation of EIS, and specifically of HFR, can guide the calibration by providing additional constraints to the solution.…”

mentioning

confidence: 99%

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Reliable Thermal-Physical Modeling of Lithium-Ion Batteries: Consistency between High-Frequency Impedance and Ion Transport

2023

Self Cite

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Among lithium-ion battery diagnostic tests, electrochemical impedance spectroscopy, being highly informative on the physics of battery operation within limited testing times, deserves a prominent role in the identification of model parameters and the interpretation of battery state. Nevertheless, a reliable physical simulation and interpretation of battery impedance spectra is still to be addressed, due to its intrinsic complexity. An improved methodology for the calibration of a state-of-the-art physical model is hereby presented, focusing on high-energy batteries, which themselves require a careful focus on the high-frequency resistance of the impedance response. In this work, the common assumption of the infinite conductivity of the current collectors is questioned, presenting an improved methodology for simulating the pure resistance of the cell. This enables us to assign the proper contribution value to current collectors’ resistance and, in turn, not to underestimate electrolyte conductivity, thereby preserving the physical relation between electrolyte conductivity and diffusivity and avoiding physical inconsistencies between impedance spectra and charge–discharge curves. The methodology is applied to the calibration of the model on a commercial sample, demonstrating the reliability and physical consistency of the solution with a set of discharge curves, EIS, and a dynamic driving cycle under a wide range of operating conditions.

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“…This setup is employed in all the measurements required for model parameter identification and reliability validation. Details on the testbench are provided in publication [16].…”

Section: Experimental Testbenchmentioning

confidence: 99%

Section: Physical Modelmentioning

confidence: 99%

mentioning

confidence: 99%

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Reliable Thermal-Physical Modeling of Lithium-Ion Batteries: Consistency between High-Frequency Impedance and Ion Transport

2023

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“…In comparison to a standard discharge-based calibration process, the proposed protocol showcased its strengths. Overall, this study underscored the significance of accurately calibrating lithium-ion battery models and proposed an innovative method that effectively addresses the challenges associated with model parameter calibration [5].…”

Section: Introductionmentioning

confidence: 99%

“…However, calibrating reliable battery models proves complex due to the multitude of involved physical parameters. To address these challenges, Rabissi, C. et al [5] conducted an extensive sensitivity analysis on the simulation of discharge, relaxation, and impedance spectroscopy tests. The focus of the analysis was on the response of the Doyle-Fuller-Newman model, which includes a thermal model to account for heat-transfer effects.…”

Section: Introductionmentioning

confidence: 99%

Thermal Behavior Modeling of Lithium-Ion Batteries: A Comprehensive Review

Madani,

Ziebert,

Marzband

2023

Symmetry

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To enhance our understanding of the thermal characteristics of lithium-ion batteries and gain valuable insights into the thermal impacts of battery thermal management systems (BTMSs), it is crucial to develop precise thermal models for lithium-ion batteries that enable numerical simulations. The primary objective of creating a battery thermal model is to define equations related to heat generation, energy conservation, and boundary conditions. However, a standalone thermal model often lacks the necessary accuracy to effectively anticipate thermal behavior. Consequently, the thermal model is commonly integrated with an electrochemical model or an equivalent circuit model. This article provides a comprehensive review of the thermal behavior and modeling of lithium-ion batteries. It highlights the critical role of temperature in affecting battery performance, safety, and lifespan. The study explores the challenges posed by temperature variations, both too low and too high, and their impact on the battery’s electrical and thermal balance. Various thermal analysis approaches, including experimental measurements and simulation-based modeling, are described to comprehend the thermal characteristics of lithium-ion batteries under different operating conditions. The accurate modeling of batteries involves explaining the electrochemical model and the thermal model as well as methods for coupling electrochemical, electrical, and thermal aspects, along with an equivalent circuit model. Additionally, this review comprehensively outlines the advancements made in understanding the thermal behavior of lithium-ion batteries. In summary, there is a strong desire for a battery model that is efficient, highly accurate, and accompanied by an effective thermal management system. Furthermore, it is crucial to prioritize the enhancement of current thermal models to improve the overall performance and safety of lithium-ion batteries.

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A coupled electrothermal lithium-ion battery reduced-order model including heat generation due to solid diffusion

Rodríguez-Iturriaga,

García,

Rodríguez-Bolívar

et al. 2024

Applied Energy

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Fast and reliable calibration of thermal-physical model of lithium-ion battery: a sensitivity-based method

Cited by 9 publications

References 64 publications

Reliable Thermal-Physical Modeling of Lithium-Ion Batteries: Consistency between High-Frequency Impedance and Ion Transport

Reliable Thermal-Physical Modeling of Lithium-Ion Batteries: Consistency between High-Frequency Impedance and Ion Transport

Thermal Behavior Modeling of Lithium-Ion Batteries: A Comprehensive Review

A coupled electrothermal lithium-ion battery reduced-order model including heat generation due to solid diffusion

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