Equivalent Circuit Parameters Research Articles

Research and Design of the RF Cavity for an 11 MeV Superconducting Cyclotron

In contrast to the room temperature cyclotron, the superconducting cyclotron’s high operational magnetic field and small extraction radius lead to a magnet design with a reduced radius. This limits the space available for the RF cavity in the 11 MeV superconducting cyclotron, necessitating a more compact RF cavity design. By using the transmission line theory, the complex structure of the quarter-wavelength coaxial cavity can be represented as a microwave circuit. Through relevant theoretical analytical formulas, equivalent circuit parameters can be derived. The resonant frequency of the RF cavity is then determined using the equivalent circuit method. The optimization of the RF cavity structure was achieved by creating a numerical model and conducting finite element numerical calculations on the high-frequency resonant system. The comparative results between the equivalent circuit and numerical calculations indicate that the frequency error remains within 0.1%, validating the compact RF cavity design. A multiple linear regression analysis facilitates the prediction of resonance frequency across various parameter variables. By analyzing the fitting formula, RF cavity machining error requirements are established, ensuring a prediction error within 1%, thus meeting engineering design criteria.

A compact Non-Quasi-Static small-signal model for GaN HEMT

In this work, we introduce a compact Non-Quasi-Static (NQS) model for the long-channel Gallium nitride high-mobility field effect transistor based on charge-based EPFL (École Polytechnique fédérale de Lausanne) HEMT model implemented in Verilog-AMS modeling language. The proposed model has been validated for the low-frequency (quasi-static) operating region as well as high frequencies up to sub-terahertz. This model has been derived from the analytical solution of the drift–diffusion and continuity equations based on physically valid assumptions. Polynomial approximation was used to make the model design-oriented and compatible with conventional circuit simulators for designing microwave circuits. Intrinsic trans-admittance parameters, obtained from the model for two devices with channel lengths of 1μm and 10μm has been validated with TCAD simulation results. Besides, the scattering parameters for the GaN HEMT equivalent circuit, have been validated with TCAD simulations and with our previous work, which already validated with experimental data. These results confirm the effectiveness of the proposed compact model for circuit simulations.

Impact of Graded AlGaN Buffer Layer Thickness on the DC, RF, Linearity, Intermodulation and Off-State Breakdown Characteristics of AlGaN Channel HEMT

This study examines the extraction of small-signal equivalent circuit parameters, linearity and intermodulation metrics, and capacitance–voltage characteristics for both AlGaN and GaN channel HEMTs. Compared to GaN channel HEMTs, AlGaN channel HEMTs have better linearity and intermodulation distortion. In the instance of AlGaN channel HEMTs, the device parasitics are decreased. Additionally, the effect of graded AlGaN buffer layer thickness on breakdown characteristics and linearity is examined. For breakdown characteristics, the 200 nm-graded AlGaN buffer layer thickness yields superior results with VBOff 157 V for a thickness of 200 nm (147 V in the case of 500 nm). At 200 nm thickness, the linearity and intermodulation distortion FOMs are also reasonably good, and the remaining device properties are essentially unchanged. Hence, the graded AlGaN buffer thickness can be reduced for high-voltage applications. For higher-voltage applications, the graded AlGaN buffer thickness can, therefore, be decreased.

Environmental Effects on Parameters of Leakage Current Equivalent Circuits of Outdoor Insulators

The performance of outdoor insulators in transmission lines may deteriorate due to aging and can even be enhanced by the presence of pollutants. Leakage current (LC) measurement is one of the most effective methods to diagnose the insulator condition, utilizing LC parameters such as magnitude and total harmonic distortion (THD). However, research on the interpretation of these parameters is still limited. This paper discusses the diagnostic method by simulation, employing the LC equivalent circuits of different types of insulators and examining the influence of environmental factors, such as humidity and pollutant levels. LC waveforms are first obtained through experiments on various insulator types, including traditional ceramic and glass insulators, advanced composite insulators, or the hybrid type of RTV silicone rubber-coated and conducting glazed insulators. Subsequently, simulations on the LC circuits of Suwarno’s and Kizilcay’s models are performed to obtain similar LC waveforms and properties. The values of the equivalent circuit parameters are then used to diagnose each insulator’s characteristics and environmental effects. The results indicate that composite insulators of epoxy resin or SiR have a larger intrinsic resistance of ~40 GΩ and nonlinear resistance (a few MΩ to tens of GΩ), representing high surface resistance of the insulators against water and pollutants. A comparison of these parameters is expected to indicate the severity levels of insulator condition. Doi: 10.28991/ESJ-2024-08-01-022 Full Text: PDF

Design and analysis of battery management system in electric vehicle

The usage of electric vehicles is gaining momentum in recent time’s thus providing support to the growth in sales of electric vehicles. The Battery management system is the most important aspect to ensure the smooth functioning of an electric vehicle. This research highlights some key statements on the background of electric vehicles. The increase in the overall growing importance of electric vehicles has also been explained in this work. Battery management system has an importance in the functioning of electric vehicles, thus presenting the key highlights of this article. The finding presents the importance of batteries and their type used in EVs. The simulation results of the Lithium battery cell – 1 RC, 2 RC equivalent circuit parameters such as charging current, terminal voltage, state of charge, and battery current have been simulated and analysed in Matlab. The future scope of BMS and its development has been discussed.

Simultaneous diagnosis of cell aging and internal short circuit faults in lithium-ion batteries using average leakage interval

Accurate health diagnostics of lithium-ion batteries are indispensable for efficient utilization. A decrease in battery capacity not only diminishes the energy efficiency but also causes several detrimental effects, such as an internal short circuit (ISC) fault; these fault can lead to thermal runaway. However, the simultaneous impact of aging and ISC faults complicates the ability to distinguish between two factors within a singular discharging or charging process. This study focuses on the co-diagnosis of battery capacity and ISC faults, emphasizing that the amount of leakage current attributable to an ISC fault remains consistent at intervals where the average voltage is identical during discharging and charging procedures. To perform this analysis, different equivalent circuit models and parameter tables are employed for the discharging and charging processes separately. Subsequently, the ISC fault and capacity are estimated using the estimated state of charge (SOC) of intervals. The practicality of the proposed method is evaluated through experiments under various dynamic profiles, ISC fault severities, aging degrees, and temperature conditions. The results substantiate the proposed method’s efficacy in co-diagnosing the capacity and ISC faults. Therefore, this method represents an advancement in the ongoing efforts to ensure the safe and effective deployment of lithium-ion batteries.

Electrochemical Impedance Spectrum Equivalent Circuit Parameter Identification Using a Deep Learning Technique

Physical models are suitable for the development and optimization of materials and cell designs, whereas models based on experimental data and electrical equivalent circuits (EECs) are suitable for the development of operation estimators, both for cells and batteries. This research work develops an innovative unsupervised artificial neural network (ANN) training cost function for identifying equivalent circuit parameters using electrochemical impedance spectroscopy (EIS) to identify and monitor parameter variations associated with different physicochemical processes that can be related to the states or failure modes in batteries. Many techniques and algorithms are used to fit a predefined EEC parameter, many requiring high-human-expertise support work. However, once the appropriate EEC model is selected to model the different physicochemical processes associated with a given battery technology, the challenge is to implement algorithms that can automatically calculate parameter variations in real time to allow the implementation of estimators of capacity, health, safety, and other degradation modes. Based on previous studies using data augmentation techniques, the new ANN deep learning method introduced in this study yields better results than classical training algorithms. The data used in this work are based on an aging and characterization dataset for 80 Ah and 12 V lead–acid batteries.

Modified Induction Machine Equivalent Circuit Including Solid Shaft Eddy Currents

The shaft eddy currents cause a significant saturation in two-pole induction machines (IMs) as they generate an opposing field and repulse the main flux, thus tightening the flux path. This results in inaccurate performance estimations with the magnetizing inductance measured in no-load conditions when the machine is loaded. This article presents a modified IM equivalent circuit considering the rotor back iron saturation effects caused by the solid shaft eddy currents using experimental measurements and recursive parameter estimation techniques. The classical equivalent circuit (CEC) parameters are determined with the standard test techniques followed by the parameter estimation of the newly introduced modified equivalent circuit (MEC) parameters. The proposed modified equivalent circuit is benchmarked with CEC and finite element analysis (FEA) simulations with and without considering eddy effects. The proposed MEC model and the FEA that consider eddy effects performed better than the other models and yielded a negligibly small error over a wide range of loading conditions. Compared to the FEA, the proposed MEC estimates the IM performance much faster, which makes it more appealing for IM performance estimations.

A whale optimization detection (WOD) method for bladder volume estimation with bioelectrical impedance spectroscopy (BIS)

A whale optimization detection (WOD) method is presented for rapid bladder volume estimation with bioelectrical impedance spectroscopy (BIS). Firstly, the WOD method for bladder volume estimation is established, which includes a bladder volume estimation electrical equivalent circuit (EEC) model and a rapid fitting strategy. Secondly, an abdominal phantom is constructed, which consists of an abdominal cavity shell and four bladders with volumes of V b = 30 ml, 100 ml, 200 ml, and 300 ml. Next, BIS experiments are conducted using the phantom with the WOD method fitted to the obtained data. The results demonstrated a high linear correlation coefficient R 2 > 0.987 between the experimental and WOD results. Finally, in vivo testing is performed using both the Caresono HD-5 ultrasonic bladder scanner and the proposed WOD method. The EEC parameters obtained by the WOD method form a mathematical formula that accurately describes the subject’s bladder volume, with a detection correlation coefficient r = 98.71%, and the maximum relative error δ = 5.88% between WOD and ultrasound testing results. In conclusion, the proposed method is expected to be applied for rapid monitoring of patients’ bladder volume.

Electrochemical Impedance Spectrum (EIS) Variation of Lithium-Ion Batteries Due to Resting Times in the Charging Processes

The electrochemical impedance spectrum (EIS) is a non-destructive technique for the on-line evaluation and monitoring of the performance of lithium-ion batteries. However, the measured EIS can be unstable and inaccurate without the proper resting time. Therefore, we conducted comprehensive EIS tests during the charging process and at different state of charge (SOC) levels with various resting times. The test results revealed two findings: (1) EIS tests with a constant long resting time showed a clear pattern in the impedance spectral radius—a decrease followed by a slight increase. We analyzed the impedance data using an equivalent circuit model and explained the changes through circuit parameters. (2) We examined the effect of resting time on impedance at consistent SOC levels. While low SOC levels exhibited significant sensitivity to resting time, medium SOC levels showed less sensitivity, and high SOC levels had minimal impact on resting time. The equivalent circuit parameters matched the observed trends. Kramers–Kronig transformation was conducted to assess the reliability of the experiments. This study not only summarizes the relationship between the EIS and SOC but also highlights the importance of resting time in impedance analysis. Recognizing the role of the resting time could enhance impedance-based battery studies, contribute to refined battery status evaluation, and help researchers to design proper test protocols.

Analysis of Offline Transient Power Oscillation and Its Suppression Method in the Microgrid with Multiple Virtual Synchronous Generators

When multiple Virtual Synchronous Generators (VSGs) operate in parallel in an islanded grid, power and frequency oscillations will occur when one VSG goes offline. However, the existing literature does not cover the related analysis and transient suppression schemes for this scenario. To analyze these complex high-order system dynamics, this paper first establishes an intuitive equivalent circuit model for multiple VSGs, and the frequency domain expressions of the multi-machine VSG system during the VSG offline transient simulation are then derived. Based on the multi-VSG model and its transient oscillations analysis, this paper further proposes a configuration scheme for the equivalent circuit parameters. Equivalently, the virtual inertia, damping coefficient and virtual impedance of the VSGs can be configured. With the proposed parameter configuration scheme, the power oscillation during the VSG offline transient can be eliminated, as verified by experiments with a microgrid lab platform using three VSGs. Compared with the existing multi-VSG studies, the proposed scheme is not only the first attempt to study the transient suppression when a VSG goes offline, but also is more intuitive in analysis and less complicated in the controller parameter tuning.

Determination of Electrode Kinetics Parameters from Dynamic Electrochemical Impedance Spectroscopy Measurements via Potential-Program Invariant Functions.

Dynamic electrochemical impedance spectroscopy, dEIS, comprises repetitive impedance spectrum measurements while slow scan-rate voltammetry is running. Its main virtue is the short measurement time, reducing the danger of contamination of the electrode surface. To further the use of dEIS, we have recently elaborated a set of theories aimed at the related data processing for three groups of fundamental electrode reactions: diffusion-affected charge transfer, charge transfer of surface-bound species, and adsorption-desorption. These theories yielded equations by which the voltammograms can be transformed to potential-program invariant forms, allowing an easy calculation of the rate coefficients; similar equations have been derived for the potential dependence of equivalent circuit parameters obtained from the impedance spectra. In this Perspective, the above derivations are condensed into a single, unified one. The theory is recommended to evaluate electrode kinetic measurements, particularly when the potential dependence of rate coefficients is under study.

Moisture Content Detection of Tomato Leaves Based on Electrical Impedance Spectroscopy

ABSTRACT The rapid detection of moisture content in tomato leaves can provide an important basis for tomato cultivation. Compared with spectroscopy technology, image technology, and dielectric detection technology, electrical impedance spectroscopy (EIS) has the potential to analyze the internal components of leaf microstructure qualitatively and quantitatively, and the characteristics of fast detection and low cost. The moisture content in tomato leaves was detected effectively and accurately at the anthesis of the first inflorescence using the EIS method. The influence of reduction of moisture content on the impedance characteristics and equivalent circuit parameters was analyzed. The frequencies of different impedance characteristics were selected based on the out-of-bag (OOB) importance. Different regression algorithms, including partial least square regression (PLSR), back-propagation neural network (BPNN), and random forest (RF), were used for estimating the leaf moisture content (LMC). The LMC models based on different impedance characteristics and different methods were established and compared. The results demonstrated that the impedance modulus in the low-frequency region, the extracellular resistance (R e), and the intracellular resistance (R i) increased first and then decreased with the decrease in the moisture content of the tomato leaves. The RF model established with the combination data had the best performance, with the coefficient of determination (R 2), normalized root-mean-square error (NRMSE), and the ratio of performance of deviation (RPD) for prediction being 0.8861, 6.02%, and 2.95, respectively. Therefore, the EIS method combined with RF was a feasible and effective method to predict LMC, providing a promising tool for moisture content detection.

PV module single–diode model, parameter extraction of polycrystalline and amorphous solar panel

Solar energy is a good option to replace the fossil driven energy market. Research is still ongoing to make solar technologies more efficient and affordable. Modeling is key in this area. Parameter extraction of PV modules enables easier simulation and accurate modeling of various PV cells/modules. The parameters are namely: (I) the photo generated current, ????????ℎ, (II) the reverse saturation current, ????????, (III) ideality factor, n, (IV) the series resistance, ???????? and (V) the shunt resistance, ????????ℎ. This research work extracted the equivalent circuit parameters of polycrystalline and amorphous solar panels. An 11 V polycrystalline and 6 V amorphous solar panels were illuminated with a 500 W halogen lamp to generate I-V characteristics with the aid of a data capture device. A Matlab/Simulink model was modified using the single diode equation to model the two test solar panels. The Orthogonal Distance Regression (ODR) method from the origin lab was adopted to solve the nonlinear/transcendental equation of the solar cell/module with the single diode model to determine the parameters of a polycrystalline and amorphous solar panel. The results show a variation in the parameters of the two test solar panels. The polycrystalline indicates a higher ????????ℎ and ????????ℎ with low ???????? and n values, which result to high efficiency. The amorphous panel shows higher n and ???????? values, which makes it have low efficiency. The polycrystalline solar panel has smaller residual sum of square (RSS) which makes it a better retrieval while the amorphous solar panel has a higher residual sum of square (RSS), the ODR method for polycrystalline was more accurate than the amorphous solar panel as observed from the validation results of the two test panels.

Cut‐set matrix methods for frequency response analysis curves of lumped parameter equivalent circuit model of three‐winding power transformer

SummaryTo accurately and efficiently calculate the frequency response of the lumped parameter equivalent circuit model (LPECM) of a transformer winding is the basis for studying the simulation method of the frequency response analysis (FRA). In this paper, two different cut‐set matrix (CSM) methods, including fundamental cut‐set (FCS) and independent cut‐set (ICS) matrix methods, are proposed to calculate the FRA curves of the LPECM of a three‐winding power transformer. First, based on graph theory and electrical circuit laws, the basic CSM equation is deduced. Second, four different FCS matrix selection methods of the LPECM are introduced and the best FCS matrix is determined by deeply analyzing their characteristics. Then, an ICS matrix method is proposed to obtain the ICS of the LPECM. Furthermore, FCS and ICS are taken into the CSM equation to calculate the FRA results of the LPECM, respectively. Finally, the accuracy of the proposed methods is validated by Multisim software and the performance of these two methods is compared with node voltage matrix (NVM) method by analyzing the calculation time. The results show that FCS and ICS matrix methods both can be used to accurately obtain the FRA results of the LPECM of the three‐winding power transformer, but ICS is more simple than FCS matrix method due to avoiding the procedure for the selection of the tree. In addition, since ICS matrix method has the shortest running time among these methods, it can be used to improve the calculation efficiency of the FRA curves of the LPECM of a three‐winding power transformer.

Evaluating the potential of Distribution of Relaxation Times analysis for plant agriculture

The analysis of a Distribution of Relaxation Times (DRT) has proven to be extremely effective for the study of electrochemical power sources. Biological systems are non-inductive, making them very suitable candidates for DRT analysis, as demonstrated by recent research. In this work, we conduct the first evaluation of DRT analysis in agricultural applications. We revisit published equivalent electrical circuit parameter data to evaluate the potential of DRT analysis for various plant electrochemical impedance spectroscopy applications. We investigate the advantages and limitations of adopting this emerging analysis method as an impedance modelling strategy for the electrochemical characterisation of plants. We illustrate its promise by comparing it with the standard methods using simulations and measurements published in the literature on fruit ripening, plant stress, and post-harvest processing of agricultural products. This study highlights the potential of DRT analysis as an effective modelling strategy for impedimetric system characterisation in agriculture, with promising advantages over standard techniques.

Accurate Electromagnetic Force Analysis of Offshore Wind Power Transformer Windings Based on Fractional Order Lumped Parameter Model

Accurate calculation of the electromagnetic force distribution of transformer windings under different loads and fault conditions is of great significance for transformer maintenance, condition evaluation and life prediction. Due to the influence of offshore wind power systems, offshore wind power transformers have high harmonic content and large changes in load rates, which can easily cause the coil destabilization, winding deformation or even damage because of the uneven distribution of the electromagnetic force. To improve the accuracy of electromagnetic force calculation, this paper proposes a fractional order numerical method. First, a three-dimensional axisymmetric transformer model and a symmetrical lumped parameter equivalent circuit model are established, respectively, based on field-circuit coupling. Second, the fractional order approximation of circuit components is realized by using the improved Oustaloup filter. In the fractional order model, the transformer is replaced by the lumped parameter equivalent circuit model. Third, as in the calculation process for integer order electromagnetic force, the integer order current has a large error, and the current waveform does not match the actual power frequency. The fractional order current and electromagnetic force at the 0.9 order are closer to the rated value. Finally, the effects of different load rates, three-phase short circuits and harmonic conditions are studied with the fractional order model. Compared with the traditional integer order finite element electromagnetic model, the fractional order equivalent circuit model established in this paper is more accurate and suitable for electromagnetic force calculation. The proposed method is significant for the structural design and state detection of transformers and also could be applied in the analysis of other dry-type transformers.

Identification of parameters for equivalent circuit model of Li-ion battery cell with population based optimization algorithms

As EVs are sold to worldwide area with different latitudes, it also implies that lithium-ion batteries need to be safely operated in different climatic environments. To ensure the robustness and safeness of EVs, the characteristics of lithium-ion batteries must be taken into considerations. To comprehensively grasp the key information of battery cell in an efficient way, building a battery model is one of the most effective ways. Based on the model, one can get rid of time-consuming experiments. Moreover, the model enables to simulate and observe battery behaviors under extreme test condition safely. In this paper, an equivalent electric circuit (EEC) of a Li-ion battery cell is investigated. Based on 2nd order RC circuit, an Extended Hybrid Pulse Power Characterization (EHPPC) is designed and carried out to observe the dynamic response of battery cell in time domain. Once substantial measurement results are obtained, the parameterization turns out to be an important issue. This paper investigates the most appropriate metaheuristic based method to rapidly and systematically identify the EEC parameters. Totally four different methods, namely Particle Swarm Optimization, Grey Wolf Optimizer, Harmony Search, and Golden Eagle Optimization, are realized and equally compared by 100 implementations. Eventually, a mission profile of driving pattern, Dynamic Stress Testing (DST), is used to validate the proposed EEC model. The 2RC EEC model is able to simulate battery voltage response with root-mean-squared error as low as 0.0045.

Study on the performance of spherical collision triboelectric nanogenerator

The development of the theoretical model for the spherical collision triboelectric nanogenerator (SC-TENG) has been slow, despite its ability to generate electric energy through low-frequency vibration while simultaneously reducing the motion response of the primary system. Previous theoretical models have solely focused on energy harvesting, disregarding the damping effect of spherical collisions. This paper presents an electromechanical coupling control equation, which accounts for the dynamic and electrical characteristics of spherical particles, to describe the relationship between motion displacement, velocity, acceleration, and particle number. The particle motion process is divided into two phases: non-collision and collision process. Using the constant velocity before and after collision, this paper calculates voltage and current changes corresponding to two collisions of particles in one cycle. Cadence software simulates and analyzes the equivalent circuit parameters of the TENG, where output voltage is proportional to the resistor/capacitor. Single, two, and three-particle acceleration, velocity, and displacement before and after collision are simulated using Abaqus software. Particle collision simulation shows the energy loss is related to the number of particles, the more the number of particles, the more the energy loss. The single-degree-of-freedom experimental model tests vibration reduction and energy collection effects of particles. As mass ratio increases, the vibration reduction and energy collection effects improve for particles. If the mass ratio remains constant, the vibration reduction effect does not vary much for different particle diameters (10/12/15 mm), but the energy collection effect of particle diameter of 10 mm is superior. Multi-layer particles, vibration control, voltage and current increase linearly with the number of layers. SC-TENG can be applied in the future to reduce structural vibration, while its additional energy collection capabilities can be as self-powered sensing to monitor movement of vibrating structures in real-time.

Non-Intrusive Efficiency Estimation of Inverter-Fed Induction Motors

The use of inverter supplies over sinusoidal supplies for induction motors is growing considerably. Inverter supplies enable effective and robust control of induction motors in many automated systems. However, this benefit features at the expense of additional harmonic motor losses due to pulse-width modulated (PWM) voltages and currents produced by inverter supplies. The quantification of these additional harmonic losses and the estimation of efficiency in a non-intrusive manner can be quite challenging. This paper proposes a non-intrusive efficiency estimation technique for inverter–fed induction motors that is based on harmonic regression analysis, harmonic equivalent circuit parameter estimation and harmonic loss analysis using limited measured data. The efficiency results from the proposed technique are comparable to those obtained using the IEC 60034-2-3 Standard up to 1% accuracy when tested on three different inverter-fed motors at different loads.