High Frequency Model Research Articles

High Frequency Permeability Measurements and Modeling of Magnetic Powder Cores Under DC Bias

High Frequency Permeability Measurements and Modeling of Magnetic Powder Cores Under DC Bias

Lightning surge analysis for cascaded H-bridge converter-based battery energy storage system

The lightning overvoltage in the cascaded H-bridge converter-based battery energy storage system (CHBC-BESS) is investigated in this paper. The high frequency (HF) model of CHBC-BESS is firstly developed. Four lightning strike cases are analyzed, including lightning striking the wind turbine (WT) blade, the transmission tower in the wind farm (WF), and the terminal tower of 35 or 220 kV grid. The influences of BESS layout schemes, lightning protection devices and line surge arresters (LSAs) are discussed. The results indicate that the surge originating from the 35 kV grid induces the highest overvoltage, with peak voltages of 496.54 kV at the grid side of the series reactor and 57.27 kV at the AC terminal of the CHBC-BESS. Though the reactor provides surge protection for CHBC-BESS, extreme conditions may still lead to a failure in the power conversion system (PCS). Additionally, overvoltage risks increase when the power modules (PMs) and battery clusters are dispersed; specifically, the peak voltage across AC terminals of submodule 1 (SM1) rises from 1.70 to 3.43 kV.

Design, modeling, and fabrication of high frequency Oersted lines for electron spin manipulation in silicon based quantum devices

Coherent manipulation of electron spins is one of the central challenges of silicon-based quantum computing efforts. Electron spin resonance (ESR) lines, or Oersted lines, allow 10–60 GHz radio frequency (RF) pulses to induce an electromagnetic field that drives Rabi oscillations in a quantum dot interface. The frequency of these Rabi oscillations is directly proportional to the strength of the induced electromagnetic field. We outline a methodology for the design of a printed circuit board and an ESR line that is able to transmit an RF pulse in the 40 GHz regime and induce an oscillating magnetic field onto a qubit device. We propose and implement a novel design by coupling a second symmetrical Oersted line in the opposing direction of the first to act as an antenna for the purpose of monitoring power and magnetic field strength at the embedded device interface.

Sweep frequency response analysis of three-phase induction motors using high frequency circuit model

Three-phase induction motor (TPIM) is one of the most important and expensive component in many industries. If a failure happens in service, the impact can be far reaching. Resulting in prolonged downtimes and expensive repairs. Sweep frequency response analysis (SFRA) is a new method that is being proposed to assess the condition of windings in motors. This paper proposes an approach for measuring the SFRA of the TPIMs using its high frequency (HF) circuit model. It also introduces an easy and efficient way to estimate the parameter values of the HF model based on the data from the SFRA test. The method first simulates the HF model and then aligns the simulated SFRA curve with the experimental one by adjusting the parameter values. This adjustment is based on individual parameter effects on the SFRA signature. The aim of this paper is to understand the SFRA signatures of TPIMs by using both experimental and simulation methods. SFRA measurements are carried out on two TPIMs (1 HP and 3 HP) under the same phases (U1U2, V1V2, W1W2) and different phase connections (U1V1, U1W1, V1W1). This paper utilizes two statistical indicators, Absolute Sum of Logarithmic Error (ASLE) and Correlation Coefficient (CC), for interpreting SFRA signatures. The CC values, ranging from 0.98 to 0.99, and the ASLE values, between 0.4 and 1.5 dB, indicate a good agreement between the measured and simulated SFRA signatures. This validates that the proposed HF model is accurate and can be applied to SFRA measurements for any rating of TPIM. This accuracy is verified in this paper using two different rating TPIMs.

Frequency experimental identification approach for single-phase induction motor common-mode parameters

Introduction. The presence of broad-spectrum and high-amplitude electromagnetic interference (EMI) within a single-phase induction motor (SPIM) drive poses a significant threat to both the system and other electronic equipment. High-frequency (HF) models of electrical motors play a critical role in overcoming these challenges, as they are essential for characterizing electromagnetic compatibility (EMC) in drives and designing effective EMI filters. The novelty of this study proposes an enhanced HF motor model based on transfer functions (TFs) to accurately represent the motor’s behavior at HFs for frequency-domain analyses in the range of 100 Hz to 30 MHz. Purpose. The equivalent HF model for a SPIM is discussed in this paper. The suggested equivalent circuit describes a motor’s common-mode (CM) properties. Methodology. HF model was developed by a frequency-domain analysis utilizing an experimental setup and MATLAB software. The motor impedance analysis is based on the measurement of variations in motor characteristics as a function of frequency in the CM setup. Originality. TF has been tuned using an asymptotic identification method of Bode to match the behavior of the real impedances of the motor parameters as a function of the frequency in the CM configuration. This tuned TFs are then synthesized into a comprehensive wideband EMC equivalent circuit model using the Foster network technique, which can be then simulated in any Spice-based simulator tools. Results. The proposed mathematical model was employed to conduct simulations, and the resulting predictions were validated against experimental data. CM response of the EMC equivalent circuit at low, medium, and HFs were compared between simulations and experimental measurements using Lt-Spice simulator software. Practical value. It is observed that results show satisfactory agreement with the measurements over a large frequency bandwidth [100 Hz–30 MHz], and the equivalent model of SPIM can be cascaded with other electronic and electrical modules to form a complete single-phase electric drive system model for fast analysis and prediction of system level EMI and electromagnetic sensitivity. References 37, table 5, figures 13.

High Frequency Modeling of Electric Machines Using Finite Element Analysis Derived Data

The use of wide band gap semiconductor switching devices in electric machine drives leads to a significant increase in power density and efficiency compared to conventional silicon-based solutions. However, this technology also presents challenges for the insulation design of electric machines since partial discharges (PDs) may occur due to high peak voltage stress as a result of fast and high frequency switching. To evaluate the risk of PD, it is necessary to understand the voltage distribution within the windings and associated insulation of an electric machine during converter operation. To this end a suitable high frequency model of the machine windings capable of predicting the internal voltage distribution is required. This paper proposes a method of constructing such a model based on finite element analysis (FEA) derived data. The FEA data used to parameterise the model in this work incorporates frequency dependant properties and homogenisation techniques to produce data which captures the high frequency behaviour of the machine. The developed model is compared with measurements in both frequency and time domains, demonstrating the utility and accuracy of the model.

Analysis, Calculation and Reduction of Shaft Voltage in Induction Generators

This paper presents analysis of shaft voltage in different configurations of a Doubly Fed Induction Generator (DFIG) and an Induction Generator (IG) with a back-to-back inverter in wind turbine applications. Detailed high frequency model of the proposed systems have been developed based on existing capacitive couplings in IG & DFIG structures and common mode voltage sources. In this research work, several arrangements of DFIG based wind energy conversion systems are investigated on shaft voltage calculation and its mitigation techniques. Placements of an LC line filter in different locations and its effects on shaft voltage elimination are studied with mathematical analysis and simulations.

High frequency Modelling of Cables in PWM Motor Drives by Using Polynomial Functions based Parameters

- The high frequency behaviour of the cables in pulse width modulation (PWM) motor drives is of a crucial importance in the analysis of transient overvoltages and conducted electromagnetic interference (EMI) propagation, both common and differential mode. In order to give a tool for simulation of the above cited phenomena, a new method for high frequency cable modelling is proposed in this paper. The method is based on the measurement of the impedance frequency responses of the cables in short and open circuit conditions. The lumped parameters cable behaviour is described by polynomial functions in frequency domain. For a given frequency a simple equivalent circuit representation of the cable is obtained. The proposed model is easily implemented in Matlab/Simulink and it is validated comparing the computed frequency impedance responses of the cable, loaded by either a resistive load or an induction motor, to the corresponding measured ones. Moreover, the prediction, by the model, of the overvoltage at the motor terminals in a long-cable PWM drive is performed. The proposed model are also compared with some commonly used high frequency cable models presented in technical literature.

A comparison of transformer HF models and their application to PQ analysis

. This research work is devoted to the comparison of some proposed high-frequency (HF) models of transformers and their application to power quality (PQ) studies. The models are classified according their structure, physical description and experimental methodology and set-up facilities needed to obtain the parameters.

High frequency modeling of dry type detuned reactor for transient studies: Simulation and experimental analyses

Dry-type detuned reactor (DDR) is a key component for power quality management. Improper design of DDR may result in insulation failure during power system transient events. This can be avoided by developing a proper DDR high frequency model that can accurately capture the behavior of the reactor during transients and provide better insight into its performance under various operating conditions. One of the main challenges of proper DDR modeling is the shape of the leakage flux, which is strongly dependent on the shielding effect of the foil conductors and hence affecting the winding frequency response at high frequencies. This paper proposes a high-frequency lumped equivalent circuit model for DDR with frequency-dependent parameters. The frequency-dependent inductances and resistances are calculated using anisotropic equivalent complex permeability to represent the damping effects in the core and winding. A combined analytical-finite element modelling approach is employed to calculate the winding capacitances. The accuracy of the proposed model is verified by comparing its frequency response with the experimental results obtained from a laboratory prototype. Furthermore, the impulse voltage distribution within the windings is obtained through simulation and measurement analyses to attest the robustness of the proposed model. The proposed model is expected to aid in the proper design and optimization of DDR to improve its insulation withstand capability and enhance its performance during transient events within power grids.

Sub-millisecond microfluidic mixers coupled to time-resolved in situ photonics to study ultra-fast reaction kinetics: the case of ultra-small gold nanoparticle synthesis.

We report a continuous microreactor platform achieving sub-millisecond homogeneous reagent mixing (∼300 μs) for a time-resolved study on the synthesis of ultra-small gold nanoparticles (NPs). The microreactor (coupled with small angle X-ray scattering, UV-vis, and X-ray absorption spectroscopy for in situ and in operando characterizations), operates within mixing time frames below system characteristic times, providing a unique opportunity to deepen the comprehension of reaction and phase transition pathways with unprecedented details. The microreactor channel length can be approximated to a given reaction time when operated in continuous mode and steady state. As a result, the system can be statically investigated, eliminating technique-dependent probing time constraints and local inhomogeneities caused by mixing issues. We have studied Au(0) NP formation kinetics from Au(III) precursors complexed with oleylamine in organic media, using triisopropylsilane as a reducing agent. The existence of Au(III)/Au(I) prenucleation clusters and the formation of a transient Au(I) lamellar phase under certain conditions, before the onset of Au(0) formation, have been observed. Taking advantage of the high frequency time-resolved information, we propose and model two different reaction pathways associated with the presence or absence of the Au(I) lamellar phase. In both cases, non-classical pathways leading to the formation of NPs are discussed.

Detailed high quality surface-based mouse CAD model suitable for electromagnetic simulations

Transcranial magnetic stimulation (TMS) studies with small animals can provide useful knowledge of activating regions and mechanisms. Along with this, functional magnetic resonance imaging (fMRI) in mice and rats is increasingly often used to draw important conclusions about brain connectivity and functionality. For cases of both low- and high-frequency TMS studies, a high-quality computational surface-based rodent model may be useful as a tool for performing supporting modeling and optimization tasks. This work presents the development and usage of an accurate CAD model of a mouse that has been optimized for use in computational electromagnetic modeling in any frequency range. It is based on the labeled atlas data of the Digimouse archive. The model includes a relatively accurate four-compartment brain representation (the ‘whole brain’ according to the original terminology, external cerebrum, cerebellum, and striatum [9]) and contains 21 distinct compartments in total. Four examples of low- and high frequency modeling have been considered to demonstrate the utility and applicability of the model.

Gold futures price forecast research----A combinatorial prediction method based on CEEMDAN-GARCH-SVR

In recent years, the international form has become more and more complex, and various emergencies have constantly impacted the world economy. In this context, countries in the world need to maintain the stability of the domestic economic market and reasonably avoid financial risks. Gold plays a major role for both countries and individuals, and predicting the gold price is a prerequisite for making important decisions.In this paper, with the closing price of gold futures AU9999 from January 2,2008 to February 13,2023 as the research object. This paper mainly uses the traditional time series model for modeling, combined with the machine learning method, and introduces the decomposition reconstruction algorithm, hoping to achieve a better prediction effect. The traditional time-series model-error t-based ARIMA (2,1,2) -EGARCH (1,1) was established, and then the machine learning method SVR was used to model the data. In order to improve the performance of the model, this paper uses the CEEMDAN method to decompose the price sequence, and then decompose the IMF according to the high frequency sequence judgment condition summary into high frequency, low frequency and remaining term three sequence, make the original complicated sequence relatively simple, then with the traditional time series model for high frequency and low frequency modeling, SVR for the remaining term. Finally, we found that the decomposition modeling algorithm proposed here has the best prediction effect and made reasonable suggestions according to the prediction results.

Study of High Frequency Characteristics Modeling and EMI Suppression of Common Mode Chokes

This paper proposes a method for building a high-frequency model of common-mode chokes in the frequency range of 9kHz to 200MHz. The method only needs to measure the common mode and differential mode impedance data of the common mode choke, and then use the differential evolution algorithm to process the impedance data to complete its high-frequency modeling. Comparison with the high-frequency model obtained by using a genetic algorithm shows that the method has high accuracy. After the high frequency modeling of the common mode chokes, the high frequency modeling of the X and Y capacitors is performed using the differential evolution algorithm, and the high frequency model of the EMI filter is obtained by combining it with the established high frequency model of common mode chokes. By comparing the measured and simulated conducted interference noise suppression effect of the EMI filter, the high frequency model of the common mode chokes is verified to suppress the conducted interference, and the effectiveness of the common mode choke high frequency modeling method is determined.

A Novel Square-Wave Voltage Injection Based Sensorless Control Method Robust to Single Open-Phase Fault for Dual Three-Phase IPM

The sensorless control for dual three-phase motors (DTMs) under faulty conditions are insufficiently studied in previous research. This research aims to investigate the effects of single open-phase faults (SOFs) on the high-frequency (HF) injection (HFI)-based sensorless control for a DTM and present a new sensorless control method robust to the SOFs. Firstly, the HFI-based sensorless control is introduced into the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">αβ</i> -subspace, where responded HF currents can reflect changes of two sets of three-phase windings simultaneously. Next, an HF fault analysis method is given to simplify the analysis process by making the inductance matrixes in the HF models unchanged under healthy and faulty conditions. Besides, an equivalent coordination method is proposed to extend the result under the phase-A SOF to an arbitrary SOF, avoiding repetitive derivation and obtaining a generalized conclusion directly. The SOFs cause the negative sequence components and varying amplitudes in the HF currents, resulting in large rotor position estimation errors. Then, a new rotor position estimation method based on a modified adaptive filter is presented to suppress these effects, which is robust to the SOFs without any fault diagnosis. The validity of the proposed analysis methods and sensorless control methods are all verified on a prototyped DTM.

Measuring and modeling diel oxygen dynamics in a shallow hypereutrophic estuary: Implications of low oxygen exposure on aquatic life

Hypoxia, or low dissolved oxygen (DO) is a common outcome of excess nitrogen and phosphorus delivered to coastal waterbodies. Shallow and highly productive estuaries are particularly susceptible to diel-cycling hypoxia, which can exhibit DO excursions between anoxia (DO ≤1 mg L−1) and supersaturated concentrations within a day. Shallow estuaries exhibiting diel-cycling hypoxia are understudied relative to larger and deeper estuaries, with very few mechanistic models that can predict diel oxygen dynamics. We utilized continuous monitoring data and the Coastal Generalized Ecosystem Model (CGEM) coupled with an Environmental Fluid Dynamics Code (EFDC) hydrodynamic model to simulate diel DO dynamics in Weeks Bay, AL. Low oxygen conditions ranging from anoxia to DO ≤4 mg L−1 were consistently observed and simulated in the lower water column for periods of minutes to >11 h. High frequency observations and model simulations also identified significant vertical gradients in near bottom DO that varied as much as 0.8 to 3.1 mg L−1 within 0.4 m from the bottom. This spatiotemporal variability presents unique challenges to adequately quantify DO dynamics and the potential exposure of aquatic life to low oxygen conditions. Our results demonstrate the need for detailed measurements to adequately quantify the complex DO dynamics in shallow estuaries. We also demonstrate that simulation models can be successfully applied to evaluate diel oxygen dynamics in complex estuarine environments when calibrated with fine time scale data and effective parameterization of water column and benthic metabolic processes.

High frequency modelling of electric motor vibration in the presence of adhesive bonded components

Electric motors often include adhesive joints to bond magnets to shells. In this paper, the variability of the frequency response function is assessed with regards to high frequency, finite element modelling and validation. The adhesive bond is used to fix the permanent magnets to the motor shell for the typical PMDC motor as it provides a smoother, more continuous surface than fixings without discontinuity of the magnetic field. To obtain the dynamic response of the motor housing at specified settings of the adhesive layer, which include variations in thickness and stiffness, a finite element model is established in ABAQUS. Given the relative stiffness of the adhesive is lower, this has a significant effect on the overall stiffness of the casing, for a fixed mass and thus the response frequencies and loss factor. When using frequency response functions to couple motors to components, this variability can be significant and thus this work is useful for the e-motor noise optimization at its design stage.

High Frequency Model of Power Transformer Bushing for Very Fast Transient Studies

High Frequency Model of Power Transformer Bushing for Very Fast Transient Studies

A Novel IGBT Junction Temperature Detection Based on High-Frequency Model of Inductor Element

Accurate online junction temperature detection of high-power insulated gate bipolar transistor (IGBT) modules is necessary for the health management system of key equipment. The voltage rise time ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$t_{\mathrm {rv}}$ </tex-math></inline-formula> ) is a good temperature sensitive electrical parameter (TSEP), which is of great significance for its accurate online extraction. In this article, a novel IGBT junction temperature detection based on the high-frequency (HF) model of inductor element is proposed. First, the equivalent model of the inductor element in the application circuit at HF is demonstrated. Second, based on the HF model of the inductor element, it is proposed and verified that <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$t_{\mathrm {rv}}$ </tex-math></inline-formula> in the IGBT turn-off process is consistent with the HF current pulse signal on the inductor element at HF, that is, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$t_{\mathrm {rv}}$ </tex-math></inline-formula> can be indirectly obtained by extracting the HF current pulse signal. Finally, the feasibility for voltage rise time extraction and junction temperature detection through HF isolation coil is verified by experiments and simulations. The research work in this article is helpful to the online junction temperature detection and has certain theoretical significance and practical engineering value.

Physics Informed Neural Network-based High-frequency Modeling of Induction Motors

The high-frequency (HF) modeling of induction motors plays a key role in predicting the motor terminal overvoltage and conducted emissions in a motor drive system. In this study, a physics informed neural network-based HF modeling method, which has the merits of high accuracy, good versatility, and simple parameterization, is proposed. The proposed model of the induction motor consists of a three-phase equivalent circuit with eighteen circuit elements per phase to ensure model accuracy. The per phase circuit structure is symmetric concerning its phase-start and phase-end points. This symmetry enables the proposed model to be applicable for both star- and delta-connected induction motors without having to recalculate the circuit element values when changing the motor connection from star to delta and vice versa. Motor physics knowledge, namely per-phase impedances, are used in the artificial neural network to obtain the values of the circuit elements. The parameterization can be easily implemented within a few minutes using a common personal computer (PC). Case studies verify the effectiveness of the proposed HF modeling method.