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Results for “equivalent circuit modeling (ECM)”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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9 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Parasitic Effects in Impedance Spectrum of PEM Water Electrolysis Cells: Case Study of High-Frequency Inductive Effects

Electrochemical impedance spectroscopy (EIS) is a powerful tool to characterize and distinguish electrochemical, electrical, and diffusive processes in an electrolysis cell. The EIS response with small impedance (mΩ) depends on components and materials of the cell, but often also on the electrical setup, cables, and connectors, leading to incorrect conclusions about the performance of the electrolysis cells. These parasitic effects are assessed via a short-circuit measurement and confirmed to be external from the membrane electrode assembly (MEA). In the setup, the inductive characteristic is described by a modified inductive reactance and must be included in the equivalent circuit model (ECM) which is fitting the cell EIS spectra in operation (in situ). If points of the spectra showing inductive characteristic (below x-axis in Nyquist plot) are excluded from the ECM evaluation, an artificially increased ohmic resistance at high frequencies is obtained. In addition, considerations on other components of the ECM can be misleading and significantly incorrect. The only way to avoid that inductive behavior caused by the external setup is incorrectly assigned to the ECM describing properties of the MEA is to include the inductive effects in the ECM analysis of in situ EIS measurements.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Miniature DC electromagnetic pumps of molten lead and sodium to support development of Gen-IV nuclear reactors

This work developed designs of submerged, dual-regions, miniature DC-EM pumps for circulating molten lead and liquid sodium at ≤500 °C without active cooling for use in ex-pile and in-pile test loops to support of materials and fuel developments for Gen-IV sodium and molten lead fast nuclear reactor. These pumps with two pumping regions are 57 mm, 66.8 mm, 95.4 mm, and 133.5 mm in diameter and have two Alnico 5 permanent magnets with Hiperco-50 pole pieces for focusing the magnetic field lines in the flow duct. The Equivalent Circuit Model (ECM) linked to the Finite Element Method Magnetics (FEMM) software in MATLAB platform calculated the pumps characteristics for a wide range of parameters. Also determined are the pumps dimensions for the highest cumulative pumping power and peak efficiency. These dimensions are the height, width, and length of the flow duct, the thickness of the Alnico magnets, the length of current electrodes, and the separation distance between the two pumping regions. For molten lead, the pumping power increases from 368 W to 728 W, and the peak efficiency from 14.7% to 31.6% with increased pump diameter from 57 mm to 133.5 mm. In conclusion, for liquid sodium, both the pumping power and peak efficiency are higher, increasing from 392 W to 767 W and from 44.3 to 51.2%, respectively, with increased pump diameter from 57 mm to 133.5 mm.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Machine Learning Benchmarks for the Classification of Equivalent Circuit Models from Electrochemical Impedance Spectra

Analysis of Electrochemical Impedance Spectroscopy (EIS) data for electrochemical systems often consists of defining an Equivalent Circuit Model (ECM) using expert knowledge and then optimizing the model parameters to deconvolute various resistance, capacitive, inductive, or diffusion responses. For small data sets, this procedure can be conducted manually; however, it is not feasible to manually define a proper ECM for extensive data sets with a wide range of EIS responses. Automatic identification of an ECM would substantially accelerate the analysis of large sets of EIS data. We showcase machine learning methods to classify the ECMs of 9,300 impedance spectra provided by QuantumScape for the BatteryDEV hackathon. The best-performing approach is a gradient-boosted tree model utilizing a library to automatically generate features, followed by a random forest model using the raw spectral data. A convolutional neural network using boolean images of Nyquist representations is presented as an alternative, although it achieves a lower accuracy. We publish the data and open source the associated code. The approaches described in this article can serve as benchmarks for further studies. A key remaining challenge is the identifiability of the labels, underlined by the model performances and the comparison of misclassified spectra.

25 ENERGY STORAGE↗
DOE OSTI2026

A Machine Learning based Approach of Estimating Equivalent Circuit Model Parameters at Different SoCs of Li-ion Batteries from Voltage Relaxation

Abstract: In this study, an approach of estimating the equivalent circuit model (ECM) parameters for Li-ion batteries (LIBs) is proposed based on the voltage value at different intervals while relaxing the LIB after discharge. The typical approach for estimating ECM parameters of a LIB is to conduct electrochemical impedance spectroscopy (EIS) measurements at different frequencies and fit them to a predefined circuit model, which requires additional measuring arrangements and specialized devices. The proposed methodology utilizes four different voltages at 0s, 60s, 360s, and 1800s alongside the specific state of charge (SoC) value for a specific constant discharge current value of ~1C until the relaxation stage to train and evaluate three regression-based machine learning models— Support Vector Regression (SVR), Extreme Gradient Boosting (XGBoost), and Gaussian Process Regression (GPR)—for estimating the ECM parameters of the selected model. Bayesian optimization is employed for hyperparameter tuning to achieve optimal performance for all the regressor models, among which, the GPR provided the best performance with the root-mean-squared error (RMSE) of less than 4x10-4 on average for the resistive components and less than 0.27 for capacitive components with excellent R2 scores. The simplicity of the approach enables it to eliminate the need for sophisticated measuring equipment and computation power.

Sagar, Md. Samiul [The University of Alabama (UA)]↗
DOE OSTI2020

Control-Oriented Modeling of Lithium-Ion Batteries

Battery management systems (BMSs), which monitor and optimize performance while ensuring safety, require control-oriented models, i.e., models tailored to the design and implementation of estimation and control algorithms. Physics-based electrochemical models describe detailed battery phenomena, but are too computationally intensive for use in estimation and control applications. Single particle models (SPMs), which retain some of the physics of electrochemical models, are often used for control-oriented battery modeling since they are computationally efficient; however, they are only valid over very low frequency ranges and C-rates. Empirical equivalent circuit models (ECMs) are also used for control-oriented battery modeling since they are computationally efficient and can describe battery behavior over wide frequency ranges; however, they provide no physical understanding of the battery and, therefore, have limited applicability. Further, fractional order terms (e.g., Warburg impedances) are often employed, making the models unwieldy for use in the time domain. This work provides a control-oriented battery model that combines the benefits of SPM and ECM models, while overcoming their limitations. The proposed model incorporates some of the battery physics found in electrochemical models, can easily be used in both the time and frequency domains, and describes battery behavior over its entire frequency range. A linearized single particle model, which incorporates key electrochemical parameters, is used for modeling battery physics at very low frequencies. For low frequencies, integer-order linear systems are used to approximate diffusion physics described by Warburg impedances, and high frequency behavior is modeled by the double layer capacitance effect. The proposed battery model is more computationally efficient than full electrochemical models since it does not require the solution of PDEs, is accurate for a wider frequency range than the SPM considered in this paper, and does not suffer from the unwieldiness and limited applicability of empirical ECMs. Finally, the model is validated in the time and frequency domains via a comparison to pseudo-two-dimensional (P2D) model simulations and experimental data.

25 ENERGY STORAGE↗
DOE OSTI2023

A mathematical approach to survey electrochemical impedance spectroscopy for aging in lithium-ion batteries

Electrochemical impedance spectroscopy (EIS) is a valuable technique to detect the health status and aging phenomena in lithium-ion batteries (LiB). Equivalent circuit modeling (ECM) is conventionally used when interpreting EIS data and gaining physical insights into the aging mechanisms. However, performing ECM is resource intensive and expert-level of knowledge is usually required to select suitable models and fitting parameters. This article presents a quick and user-friendly data analysis algorithm as an alternative to ECM by mathematically fitting geometric features in Nyquist plots and obtaining the growth trends of the features. The evolving trends in the Nyquist plots, such as chord lengths of the arcs and interception points, are consistent with the growth of resistance components obtained using ECM with R 2 values from 0.67 to 0.99, and therefore can be used as indicators of battery aging. Our results show that the quick-fitting approach is suitable for analyzing a series of EIS data acquired during battery cycling and identifying the underlying aging mechanisms.

Chen, Bor-Rong↗
NASA NTRS1991

A model for the scattering of high-frequency electromagnetic fields from dielectrics exhibiting thermally-activated electrical losses

An equivalent circuit model (ECM) approach is used to predict the scattering behavior of temperature-activated, electrically lossy dielectric layers. The total electrical response of the dielectric (relaxation + conductive) is given by the ECM and used in combination with transmission line theory to compute reflectance spectra for a Dallenbach layer configuration. The effects of thermally-activated relaxation processes on the scattering properties is discussed. Also, the effect of relaxation and conduction activation energy on the electrical properties of the dielectric is described.

Hann, Raiford E.↗
DOE OSTI2022

Failure analysis of solid oxide fuel cells nickel-yttria stabilized zirconia anode under siloxane contamination

In this study, the failure process of the solid oxide fuel cell (SOFC) Ni-yttria-stabilized zirconia (YSZ) anode is investigated with D4 siloxane (octamethylcyclotetrasiloxane) contamination. In order to evaluate the influence of the electrochemical reaction on the siloxane deposition process, the SOFC experiments were operated at open circuit voltage (OCV) and 50 mA cm -2 conditions at 800°C. During the failure process, electrochemical, morphology and exhaust gas component analysis testing are conducted at the critical points. An equivalent circuit model and corresponding microstructure parameter calculations for separated physicochemical processes were utilized for the quantitative analysis of the failure process. Further, the results confirm the siloxane chemical adsorption deposition mechanism proposed in previous work. As a result, the failure of the anode was attributed to the gas diffusion blockage by dense silicon dioxide layer formation. The anode failure process with siloxane contamination is faster when the anode is operated under polarization.

25 ENERGY STORAGE↗
DOE OSTI2026

Mechanism-Informed Breakdown: Understanding Degradation by Controlling Voltage-Hold Patterns in Proton Exchange Membrane Water Electrolyzers

Low catalyst loadings pose challenges to performance stability in proton exchange membrane (PEM) water electrolysis over extended operation. To study the impact of degradation mechanisms and voltage loss rates, different stress tests are applied to membrane electrode assemblies. Potential cycling conditions were observed to induce higher degrees of iridium (Ir) oxide crystallization, ionomer degradation, and catalyst layer (CL) thinning, which likely contributed to higher kinetic loss rates. On the other hand, while Ir migrating into the PEM (Ir band) generally impairs performance, the interconnected and more uniform Ir band formed under a constant 2 V hold may allow for Ir at the catalyst/membrane interface to remain electronically connected and kinetically accessible, as well as indicate greater Ir site access during the applied stressor. The 2 V hold also demonstrates improved kinetic durability through a lower Tafel slope, faster polarization kinetics, and reduced charge transfer resistance. In contrast, potential cycling caused the migration of disconnected Ir agglomerates into the membrane bulk and created a steady increase in charge transfer resistance, a more dramatic decrease in capacitance (46.7% loss), and significant damage to the surrounding ionomer, indicating a decline in both the quality and quantity of active sites in the anode CL. This work underscores the distinct degradation pathways associated with load holds versus cycling, highlighting the role of catalyst-ionomer interactions in kinetic performance and long-term stability. These insights can inform operational strategies for PEM electrolyzers powered by intermittent energy sources, aiming to minimize efficiency losses over extended operation.

36 MATERIALS SCIENCE↗