Global Sensitivity Analysis of the Single Particle Lithium-Ion Battery Model with Electrolyte

Grandjean, Thomas R. B.; Li, Liuying; Odio, Maria Ximena; Widanage, Widanalage Dhammika

doi:10.1109/vppc46532.2019.8952455

Cited by 14 publications

(8 citation statements)

References 40 publications

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“…We chose to tune the diffusion coefficients and maximum concentration as it has been reported in literature that they are some of the most sensitive parameters. [78][79][80] Tuning these parameters we can adjust the discharge time and the relaxation profile. We tune the 100% SOC stoichiometry because it is our initial condition and thus the only parameter to adjust the initial voltage.…”

Section: Stoichiometrymentioning

confidence: 99%

Development of Experimental Techniques for Parameterization of Multi-scale Lithium-ion Battery Models

Chen

Planella

O’Regan

et al. 2020

J. Electrochem. Soc.

342

339

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Presented here, is an extensive 35 parameter experimental data set of a cylindrical 21700 commercial cell (LGM50), for an electrochemical pseudo-two-dimensional (P2D) model. The experimental methodologies for tear-down and subsequent chemical, physical, electrochemical kinetics and thermodynamic analysis, and their accuracy and validity are discussed. Chemical analysis of the LGM50 cell shows that it is comprised of a NMC 811 positive electrode and bi-component Graphite-SiOx negative electrode. The thermodynamic open circuit voltages (OCV) and lithium stoichiometry in the electrode are obtained using galvanostatic intermittent titration technique (GITT) in half cell and three-electrode full cell configurations. The activation energy and exchange current coefficient through electrochemical impedance spectroscopy (EIS) measurements. Apparent diffusion coefficients are estimated using the Sand equation on the voltage transient during the current pulse; an expansion factor was applied to the bi-component negative electrode data to reflect the average change in effective surface area during lithiation. The 35 parameters are applied within a P2D model to show the fit to experimental validation LGM50 cell discharge and relaxation voltage profiles at room temperature. The accuracy and validity of the processes and the techniques in the determination of these parameters are discussed, including opportunities for further modelling and data analysis improvements.

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Section: Stoichiometrymentioning

confidence: 99%

Development of Experimental Techniques for Parameterization of Multi-scale Lithium-ion Battery Models

Chen

Planella

O’Regan

et al. 2020

J. Electrochem. Soc.

342

339

View full text Add to dashboard Cite

show abstract

“…The results indicate that this method offers a certain improvement in calculation efficiency and estimation results. Based on the SP model, reference [83] develops and illustrates a single particle model with electrolyte (SPME) considering the influencing effect of the electrolyte on the output voltage. By introducing the law of matter conservation in liquid electrolytes and the law of charge conservation, the model accuracy is improved.…”

Section: ) Em-based Methodsmentioning

confidence: 99%

Critical Review on Improved Electrochemical Impedance Spectroscopy-Cuckoo Search-Elman Neural Network Modeling Methods for Whole-Life-Cycle Health State Estimation of Lithium-Ion Battery Energy Storage Systems

Xiong,

Wang,

Takyi-Aninakwa

et al. 2024

Prot. Control Mod. Power Syst.

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“…The remaining parameters, such as cathode diffusion coefficient D s,p , anode diffusion coefficient D s,n , electrolyte coefficient D e , and ionic conductivity κ, are deemed to have no effect since they are one order of magnitude smaller than α (µ<0.41 mV). Furthermore, compared to the literature which analyze the sensitivity to model voltage output in the entire SoC window (Grandjean et al 2019), the sensitivity of the solid diffusion coefficients D s is insensitive. The reason may be due to the variation of SoC is negligible during a multisine-based characterization test, which leads to the effect of diffusion behaviour to terminal voltage being minor.…”

Section: Global Sensitivity Analysis -Morris Methodsmentioning

confidence: 99%

“…The results show that the maximum and minimum lithium-ion concentrations have the greatest influence on the model output. Grandjean et al (2019) identified that the most sensitive parameters of a single particle model with electrolyte (SPMe) using the Morris screening method are the anode diffusion coefficient and cathode diffusion coefficient. Most of existing SA studies focus on the effect of parameters on the output of the battery model for robustness evaluation, however, very few researchers investigate the effect of physical parameters contributing to the battery nonlinearities.…”

Section: Introductionmentioning

confidence: 99%

Understanding non-linearity in electrochemical systems using multisine-based non-linear characterization

Fan

Grandjean

O’Regan

et al. 2021

Transactions of the Institute of Measurement and Control

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Background: With the development of advanced characterization techniques, lithium-ion battery non-linearities have recently gained increased attention which can benefit battery health diagnosis and ageing mechanism identification. In comparison to conventional single sine wave-based methods, the multisine-based non-linear characterization method has the advantage of capturing the dynamic voltage response within a short testing duration, and therefore has further development potential for on-board applications. However, understanding lithium-ion battery electrochemical processes that contribute to battery non-linearities is still unclear. Methods: In this paper, the sensitivity of the Doyle–Fuller–Newman model parameters are analysed in the frequency domain to investigate the electrochemical processes that contribute to the non-linear dynamics of the voltage response. To begin with, the non-linearities of the Doyle–Fuller–Newman model with validated parameters are characterized and compared to experimental data from a commercial cell. This demonstrated a significant difference between the mathematical model and the non-linearities determined experimentally. Then, a global sensitivity analysis is applied to determine the most sensitive parameter contributing to battery non-linearities. Finally, the appropriate value of the most sensitive parameter which results in the closest non-linear response to the commercial battery is estimated through minimizing the root mean square error. Results: The results show that the charge transfer coefficient is the most sensitive parameter contributing to battery non-linearities among the Doyle–Fuller–Newman model parameters. The non-linear response of the Doyle–Fuller–Newman model is validated with good agreement with the experimental results, when the Butler–Volmer kinetic is asymmetrical due to the unequal anodic and cathodic charge transfer coefficients.

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Global Sensitivity Analysis of the Single Particle Lithium-Ion Battery Model with Electrolyte

Abstract: Please refer to published version for the most recent bibliographic citation information. If a published version is known of, the repository item page linked to above, will contain details on accessing it.

Cited by 14 publications

References 40 publications

Development of Experimental Techniques for Parameterization of Multi-scale Lithium-ion Battery Models

Development of Experimental Techniques for Parameterization of Multi-scale Lithium-ion Battery Models

Critical Review on Improved Electrochemical Impedance Spectroscopy-Cuckoo Search-Elman Neural Network Modeling Methods for Whole-Life-Cycle Health State Estimation of Lithium-Ion Battery Energy Storage Systems

Understanding non-linearity in electrochemical systems using multisine-based non-linear characterization

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