Impedance-based Modeling Research Articles

From Micro-Perforates to Micro-Capillary Absorbers: Analysis of Their Broadband Absorption Performance through Modeling and Experiments

A challenging issue is currently the design of non-fibrous ultra-thin acoustic absorbers that are able to provide broadband performance in demanding environments. The objective of this study is to compare using simulations and measurements the broadband absorption performance of highly porous micro-capillary plates (MCPs) to that of micro-perforated panels (MPPs) under normal incidence while considering unbacked or backed configurations. MCPs are unusual materials used for sound absorption with micron-sized channels and a high perforation ratio. Impedance-based modeling and Kundt tube experiments show that MCPs with suitable channel diameters have a pure constant resistance that outperforms the acoustic efficiency of MPP absorbers. Unbacked MCPs exhibit a controllable amount of high absorption that can exceed 0.8 over more than five octaves starting from 80 Hz, thereby achieving a highly sub-wavelength absorber. MCPs still provide broadband high absorption when backed by a rigid cavity. Their bandwidth-to-thickness ratio increases toward its causal limit when the cavity depth decreases. A parallel MCP resonant absorber partly backed by closed and open cavities is proposed. Such MCP-based absorbers could serve as short anechoic terminations for the characterization of acoustic materials at low frequencies.

Impedance network-based oscillatory stability analyzer (INOSA) – A frequency domain tool for investigating IBR-grid interactions

Unstable subsynchronous oscillations (SSOs) may be excited due to adverse interactions between inverter-based resources (IBRs) and series-compensated or weak ac networks. The frequency-sweep impedance modeling and analysis method is widely used for scanning grid-tied IBRs against the risk of SSO. The stability of such a system is heavily influenced by system-wide parameters such as IBR dispatching conditions (input resource, and different dispatch scenarios), and network status (short-circuit and/or series-compensation levels). The variation in the operating conditions must be taken into account when conducting frequency-scanned impedance-based modeling and analysis. This paper proposes a tool, named impedance network-based oscillatory stability analyzer (INOSA), which integrates decades of research on impedance-based analysis to investigate the risk of SSO under varying operating conditions. The INOSA tool is developed as a MATLAB application package. It takes the available system parameters and frequency-scanned impedance data as input and processes it to carry out impedance network-based stability analysis under all operating conditions. The developed tool outputs key stability information such as damping and frequency of each oscillation mode, and a multi-dimensional security boundary/region plot that can be used to assess the risk of SSO and take appropriate measures. A case study on an actual power system is presented to demonstrate the features and capability of the analysis tool.

Identifying Feasibility Region Boundaries in Power Systems With Multiple VSCs

It is anticipated that a large number of voltage source converters (VSCs) will be integrated into future power systems, which can potentially be detrimental to system stability. Previous work has utilized an impedance-based approach to analyze the feasibility region boundaries of power systems with multiple VSCs. However, impedance-based modeling limits the analysis of the system feasibility region to just two or three dimensions. Hence, this paper develops a methodology based on bifurcation theory that enables the system multi-dimensional feasibility region to be identified efficiently with consideration of multiple different varying parameters. The developed methodology is generalized so that it can be applied to identify system feasibility region boundaries in other power systems with multiple varying parameters. The partial Spearman correlation coefficient is adopted in this paper to identify the key parameters that affect the feasibility region boundary. Additionally, the calculated correlation indices quantify the interactions between the control loops VSCs in the system. The proposed methodology is verified against other analytical methods and the impact of key parameter variation on the system feasibility region boundaries is discussed.

Battery degradation diagnosis with field data, impedance-based modeling and artificial intelligence

• Electrode-level degradation diagnosis approach for lithium-ion batteries • Hybrid model integrates the battery impedance and OCV-reconstruction • Accurate parameter identification with artificial intelligence and field data • Accurate estimation of capacity fade, power fade, and degradation modes • Robustness analysis and data requirements analysis for cloud applications By collecting battery data from the field and building up the battery digital twin in the cloud, the degradation of batteries can be monitored online on the electrode level and the information regarding the degradation modes can be extracted from the data. Here, we present a degradation diagnosis framework for lithium-ion batteries by integrating field data, impedance-based modeling, and artificial intelligence, revolutionizing the degradation identification with accurate and robust estimation of both capacity and power fade together with degradation mode analysis. By integrating an impedance-based model and an open-circuit voltage reconstruction model, the hybrid model consists of parameters representing the change of impedance in a wide frequency domain and the change of open-circuit voltage during degradation. Based on the field data with low and high dynamics, the data-driven parameter identification method using a multi-step cuckoo search algorithm considering parameter sensitivity differences shows high accuracy and robustness in aging parameter estimation and degradation mode identification even under sensor noise. Furthermore, the data requirement for the battery digital twin in the sense of sampling rate was investigated considering degradation identification accuracy, computational cost, and data storage cost. This work highlights the opportunity in online electrode-level degradation diagnosis in the field through battery modeling and artificial intelligence.

Analysis of Spontaneous and Implicit Internal Self-Excitation in Aircraft Variable Frequency AC Power System Based on Dual-Stator Winding Induction Generator

The dual-stator winding induction generator (DWIG) is an alternative main generator in a variable frequency ac power system. So far, the existing studies have not covered the issue of DWIGs excitation controllability, which is a matter of importance for airworthiness. In this article, we develop an impedance-based modeling and analysis technique to investigate DWIGs excitation controllability. Two related topics are presented: the spontaneous self-excitation analysis in uncontrolled system and the implicit internal self-excitation pattern analysis in actively controlled system. In the topic about spontaneous self-excitation, a virtual impulse source technique is developed to derive the impedance-based method properly in the analysis for uncontrolled DWIG. In the second topic, the analysis performed in the presence of a closed-loop controller figures out the same underlying mechanism in both the plant's open-loop stability and the spontaneous self-excitation. The experimental results verify the proposed analysis and techniques that benefit the comprehensive understanding and practical application of DWIG-based power system.

Quantitative Mapping of Modeling Methods for Stability Validation in Microgrids

Although power electronic converters have been the key enablers for the the integration of renewable generation, heterogeneous controllers and lower inertia increase the complexity of microgrids, more likely to cause instability. Hence, it is significant to study the stability of microgrids using prospective modeling tools such as, bode plots, Nyquist plots, eigenvalue loci, etc. The modeling of microgrids is an important step of stability analysis, where state-space-based and impedance-based modeling are the two commonly used stability evaluation approaches in microgrids. Miscellaneous modeling methods have respective pros and cons, which have been investigated in the existing literatures to some extent. However, it is still critical to quantify the modeling techniques so as to formalize the stability validation in an intuitive way, which is not addressed in existing literatures. Therefore, in this paper, modeling methods for stability validation are mapped based on an order-indicated complexity, and a quantitative framework for the mapping is provided. The proposed framework can be instructive when modeling microgrid systems with different sizes, topologies or control strategies, etc., and it turns out to be well applicable as demonstrated by exemplified simulations and experimental tests.

Wireless Power Harvesting During MRI.

We present methods to harvest wireless power directly from the MRI RF field. The system includes a harvester coil to capture RF energy and an RF-DC converter for rectification. Energy harvesting by the harvester coil is modeled as a function of the MRI B1 RF field. Rectification is modeled using power-dependent large signal S-parameter simulation. A novel reference impedance-based modeling approach is leveraged to cascade models for linear inductive coupling and nonlinear diode rectification, and validated. The method permits independent optimization of harvester coils and RF-DC converters to maximize harvesting efficiency. Feasibility of this technique is demonstrated by implementing concurrent in-bore wireless power harvesting and MRI scanning on a clinical system. The effect of artifacts on image quality is also investigated.Clinical Relevance- In-bore wireless harvesting can provide power for medical accessories during MRI, with minimal system modification and cost.

Impedance-Based Modeling and Common Bus Stability Enhancement Control Algorithm in DC Microgrid

In this paper, impedance modeling of a DC microgrid system consisting of a source and load converter, including an input filter, is performed. Impedance-based modeling has been used to derive mathematical models of the output impedance of the source converter and the input impedance of the load converter. The correlation between the converter interaction and system stability is analyzed based on the mathematical model. An impedance-based stability analysis is used to determine the system stability by analyzing the interactions among the converters in the DC microgrid system. Middlebrook’s stability criterion, which uses the impedance transfer function, is applied to determine system stability. Moreover, in this paper, a stability enhancement control algorithm is proposed to resolve the system instabilities resulting from interaction among the converters and the distortion caused by the harmonics emanating from the AC input. The proposed stability enhancement control algorithm consists of a feed-forward type virtual impedance (VI) and a proportional-resonant (PR) controller. The validity of the proposed method is demonstrated by the results of the response characteristics in the frequency domain, and the effectiveness of the proposed control algorithm is verified via simulations and prototype experimental models.

Large-Signal Impedance-Based Modeling and Mitigation of Resonance of Converter-Grid Systems

Large-signal impedance of grid-connected converters can be used to predict resonance-generated distortions in converter-grid systems. Note that the large-signal impedance of a network represents its impedance response for different magnitudes of perturbation injected at its terminals. This paper presents large-signal impedance-based modeling and mitigation of resonance of grid-connected voltage source converters. Challenges of large-signal modeling because of the inapplicability of the small-signal approximation are addressed by leveraging the dominating influence of hard nonlinearities (such as pulsewidth modulation saturation and limiters) over soft nonlinearities (such as Park's transformations and phase-locked loop (PLL)) in shaping the large-signal behavior of the converter. The paper develops large-signal gains of hard nonlinearities using different types of describing functions. The paper shows that the large-signal impedance of a voltage source converter (VSC) can be shaped to reduce resonance-generated distortions by inserting limiters in the control system of the VSC. Developed large-signal impedance models are validated using numerical simulations of a VSC with dq current control and PLL. Large-signal impedance measurements of a commercial 1 MW VSC-based inverter and a medium-voltage doubly-fed induction generator with approximate 4 MW rating are presented to experimentally demonstrate the influence of the injected perturbation magnitude on the impedance response.

A dq-Domain Impedance Measurement Methodology for Three-Phase Converters in Distributed Energy Systems

A distributed energy system (DES) using controlled power electronics converters delivers power to loads, via conventional, as well as a number of renewable, energy sources. However, stability concerns retard the integration of power electronics converters into an existing DES. Therefore, due to the high penetration of power converters, the overall network analysis of DES is becoming increasingly difficult. Impedance-based DES modeling emerged as an effective technique as it reduces the system into source and load subsystems and offers easier analysis of the dynamic interactions between them. These models can be obtained using either analytical calculations, simulations, or experimental measurements. In this work, firstly, a line-to-line current injection technique is used for the measurement of alternating current (AC) impedances. Since it requires repeated injections, a d q -domain impedance measurement methodology based upon a set of independent perturbations and measurements is proposed. The perturbation is injected via a sweep signal which is preprocessed by the digital signal processor (DSP) prior to injection. The d q reference frame is synchronized with the three-phase AC system using a low-bandwidth phase-locked loop (PLL). The close matching of impedance parameters measured in simulation using the proposed approach with those obtained using analytical expressions and the line-to-line current injection technique verifies the effectiveness of the approach. Furthermore, the method was also implemented experimentally, and the close matching of the results with the analytical and simulation results validates the overall modeling and measurement procedure.

Development of a voltage-behavior model for NiMH batteries using an impedance-based modeling concept

To handle the complexity of modern automotive power nets, simulation-based design methods are important and suitable models of all system components including the battery as a main part are therefore mandatory. However, simulation models of energy storage devices are difficult to obtain. In particular, batteries are time-variant and strongly non-linear. An impedance-based modeling approach has been applied that copes with these characteristics and offers the development and parameterization of powerful models covering a wide dynamic range. As an example, this paper outlines the development of a NiMH battery model. Besides the impedance-based part of the model, the influences of the typical hysteresis effect of NiMH batteries is described in detail and an empirical modeling approach is introduced. The presented model is already successfully used by an automotive manufacturer which reflects the applicability of the modeling approach.

Supercapacitors and lithium-ion batteries for power electronic applications

This article employs the method of electrochemical impedance spectroscopy (EIS) to extend the physics-based, nonlinear equivalent circuit models of supercapacitors (SCs) to describe lithium-ion batteries (Li-ion). The following section briefly introduces the method of electrochemical impedance spectroscopy and presents measured impedance spectra. From these spectra, appropriate equivalent-circuit models are deduced. After this, the MATLAB/Simulink implementation of the new simulation models is discussed, and simulation results, as well as verification measurements, are provided. Finally, conclusions are drawn, and future perspectives of the new impedance-based modeling approach are outlined.

Applications of the Impedance Method on Multiple Piezoelectric Actuators Driven Structures

An impedance-based system modeling technique has been developed to determine the output forces of multiple piezoelectric (PZT) patch actuators on an active structure to produce a known vibration response. In the analysis of the dynamic response of a structure driven by multiple PZT patches, the proposed model includes not only the dynamic interactions between the PZT patch and the host structure but also the impedance couplings among PZT patches. Therefore this approach can apply to a structure with multiple PZT actuators. Furthermore, the bending stiffness and the thickness of a PZT patch that are proved to be important as increases of excitation frequency are included in the proposed impedance model. Examples are given to demonstrate how to synthesize a known vibration response and how to suppress vibration response at an arbitrary location on structures using this technique.