Equivalent Circuit Parameters Research Articles

РАЗРАБОТКА ПРОГРАММЫ РАСЧЕТА ПАРАМЕТРОВ СХЕМЫ ЗАМЕЩЕНИЯ ТРЕХФАЗНОГО АСИНХРОННОГО ЭЛЕКТРОДВИГАТЕЛЯ

The article is devoted to developing a program for calculating the parameters of a T-shaped equivalent circuit of three-phase asynchronous electric motors. The relevance of this work is due to the need to obtain reliable results of computer simulation modelling of electric drive systems in software packages. The aim of the study is to implement in a convenient software interface an analytical technique for calculating the parameters of an asynchronous motor equivalent circuit with minimal deviations from the catalogue data. For the software calculation of the equivalent circuit parameters the paper considers analytical approximation and iterative counting techniques, since they do not require experiments on industrial electrical equipment. A comparative analysis of such techniques is performed using the example of a three-phase asynchronous motor brand BA280S4 with a power of 110 kW. The results of the compar-ative analysis show that the highest reliability of the mechanical and electromechanical characteristics is achieved in the case of using the iterative counting technique with minimizing the objective function of the sum of the weighted squares of the deviations of the control point values from the catalogue data. The authors implement the program for calculating the equivalent circuit parameters according to the selected calculation method in the Embarcadero Delphi environment. The reliable values of the electric motor parameters calculated by the program will allow for computer to model electric drive systems that best matches real objects.

A Novel Spotted Hyena Optimizer for the Estimation of Equivalent Circuit Model Parameters in Li-Ion Batteries

Li-ion batteries possess significant advantages like large energy density, fast recharge, and high reliability; hence, they are widely adopted in electric vehicles, portable electronics, and military and aerospace applications. Albeit having their merits, accurate battery modeling is subjected to problems like prior information on internal chemical reactions, complexity in problem formulation, a large number of unknown parameters, and the need for extensive experimentation. Hence, this article presents a reliable Spotted Hyena Optimizer (SHO) to determine the equivalent circuit parameters of lithium-ion (Li-ion) batteries. The methodology of the SHO is derived from the living and hunting tactics of spotted hyenas, and it is efficiently applied to solve the battery parameter estimation problem. Nine unknown battery model parameters of a Samsung INR 18650-25R are determined using this method. The model parameters estimated are endorsed for five different datasets with various discharge current values. Further, the effect of parameter range and its selection is also emphasized. Secondly, for validation, various performance metrics such as Integral Squared Error, mean best, mean worst, and Standard Deviation are evaluated to authenticate the superiority of the proposed parameter extraction. From the computed results, the SHO algorithm is able to explore the search area up to 89% in the case of larger search ranges. The chosen model and range of the SHO precisely predict the behavior of the proposed Li-ion battery, and the results are in accordance with the catalog data.

Influence of the Bias Voltage on Effective Electron Velocity in AlGaN/GaN High Electron Mobility Transistors.

The small-signal S parameters of the fabricated double-finger gate AlGaN/GaN high electron mobility transistors (HEMTs) were measured at various direct current quiescent operating points (DCQOPs). Under active bias conditions, small-signal equivalent circuit (SSEC) parameters such as Rs and Rd, and intrinsic parameters were extracted. Utilizing fT and the SSEC parameters, the effective electron velocity (νe-eff) and intrinsic electron velocity (νe-int) corresponding to each gate bias (VGS) were obtained. Under active bias conditions, the influence mechanism of VGS on νe-eff was systematically studied, and an expression was established that correlates νe-eff, νe-int, and bias-dependent parasitic resistances. Through the analysis of the main scattering mechanisms in AlGaN/GaN HEMTs, it has been discovered that the impact of VGS on νe-eff should be comprehensively analyzed from the aspects of νe-int and parasitic resistances. On the one hand, changes in VGS influence the intensity of polar optical phonon (POP) scattering and polarization Coulomb field (PCF) scattering, which lead to changes in νe-int dependent on VGS. The trend of νe-int with changes in VGS plays a dominant role in determining the trend of νe-eff with changes in VGS. On the other hand, both POP scattering and PCF scattering affect νe-eff through their impact on parasitic resistance. Since there is a difference in the additional scattering potential corresponding to the additional polarization charges (APC) between the gate-source/drain regions and the region under the gate, the mutual effects of PCF scattering on the under-gate electron system and the gate-source/drain electron system should be considered when adjusting the PCF scattering intensity through device structure optimization to improve linearity. This study contributes to a new understanding of the electron transport mechanisms in AlGaN/GaN HEMTs and provides a novel theoretical basis for improving device performance.

Monitoring the Dilution of Buffer Solutions with Different pH Values above and below Physiological pH in Very Small Volumes.

The accurate determination of the post-dilution concentration of biological buffers is essential for retaining the necessary properties and effectiveness of the buffer to maintain stable cellular environments and optimal conditions for biochemical reactions. In this work, we introduce a silicon-based impedance chip, which offers a rapid and reagent-free approach for monitoring the buffer concentrations after dilution with deionized (DI) water. The impedance of the impedance chip is measured, and the impedance data are modeled using a multiparameter equivalent circuit model. We investigated six aqueous biological buffers with pH values above and below the physiological pH for most tissues (pH ~ 7.2-7.4) following dilution with DI water by factors of 2.0, 10.0, 20.0, 100.0, and 200.0. The impedance measurement is then performed for the frequency spectrum of 40 Hz to 1 MHz. From the interpretation of the impedance measurement using the multiparameter equivalent circuit model, we report a buffer-sensitive equivalent circuit parameter RAu/Si of the silicon-based impedance chip showing a linear trend on a logarithmic scale with the buffer concentration change after dilution. The parameter RAu/Si is independent of the buffer pH and the added volume. The results demonstrate the efficacy of the silicon-based impedance chip as a versatile tool for precise post-dilution concentration determination of diverse biologically relevant buffers. The presented impedance chip offers rapid, accurate, and reliable monitoring, making it highly suitable for integration into automated liquid-handling systems to enhance the efficiency and precision of biological and chemical processes.

A new approach towards more accurate modeling of mechanical defects in power transformer windings

In many cases, power transformers can continue their normal operation despite mechanical defects in their windings. However, estimating the lifespan and assessing the risk of using a transformer with mechanical defects depend on detailed studies of insulation aging and the distribution of transient voltages along the winding, and consequently, the likelihood of partial discharge. Risk assessment studies can only be effectively conducted through accurate modeling of transformers across a wide frequency range. In this study, an attempt has been made to investigate the impact of winding mechanical defects on the transformer equivalent circuits parameters using finite element method precisely modeling of transformer windings, without applying approximation or common simplifications. To compare the effect of each mechanical defect on the resistance, inductance, and capacitance matrices arrays, an index called fault classification accuracy has been used. The investigations have shown that the capacitance matrix arrays undergo the most significant changes for all types of modeled defects in this research. To examine the impact of defects on the transformer frequency response, a π coupled model that directly uses output matrices of finite element modeling has been employed. The sensitivity of various components of frequency response has also been investigated for the used model.

Capacitive voltage effect at a resistive sintering system container and its electrical model

Abstract The electric current activated/assisted sintering (ECAS) method enables various kinds of materials to be produced much faster and environmentally friendly compared to conventional sample production systems. The main handicap of this system is that the heating regime varies according to the material type even the chemical composition of the same type of material and causes partial melting due to the sudden current flow. Previously, the ECAS output equivalent circuit is modeled as a temperature-dependent resistor in the literature. This study shows that it is insufficient to model the ECAS output consisting of a container and two stiffs as a resistor considering experimental waveforms. We report the discovery of a capacitive effect at the output of the ECAS system that has not been reported before. We have given an equivalent electrical circuit for the ECAS system output and examined the effect’s temperature dependence. The circuit model, which consists of a parallel resistor-capacitor (R p-C) circuit in series with another resistor (R s), is suggested for the container and the stiffs. By using the experimental data, the equivalent circuit parameters are calculated by curve-fitting. The temperature dependence of the equivalent circuit parameters is also examined. Possible explanations for the capacitive effect are given. Such a model and further examining the effect may help design better ECAS systems.

Field Analysis and Equivalent Circuit Parameters of Linear Induction Motor with Eddy Current Secondary, Taking End Effect into Consideration

The field analysis of a single-sided linear induction motor (LIM) taking end effect into consideration is carried out. A suitable model is used to establish the two components of secondary current density and the air gap field intensity, these components, beside the force density are carried out through the three regions model. The drive force acting on a conducting secondary sheet is calculated and plotted as functions of the speed, taking the length of secondary ends as parameter. The motor speed can be controlled by changing the displaced angle φ of the electric loading wave in the second stator phase. The equivalent circuit parameters are determined here in terms of the machine geometry by a new suggested method. These parameters are plotted as function of the motor speed for different secondary ends.

Relating state-of-charge to impedance and equivalent circuit parameters in lithium-ion cells: An experimental study

The wide-band impedance of Lithium-ion (Li-ion) batteries has become a focal point for researchers interested in State-of-Charge (SOC) estimation and battery modeling. However, the interplay between SOC, wide-band impedance, and model parameters has not been extensively explored. This paper addresses this gap by investigating how SOC impacts the impedance and Equivalent Circuit Model (ECM) parameters of a Li-ion battery cell through empirical measurements. The study utilizes discharge tests to vary the SOC and employs the Coulomb Counting Method (CCM) to estimate the approximate SOC from the response signals. A novel measurement technique is introduced and applied to determine a cell’s wide-band impedance at different SOC levels. This innovative approach uses a Pseudo-random Impulse Sequence (PRIS) perturbation signal to measure wide-band cell impedance. The collected impedance data is then used to estimate the ECM parameters. Experimental findings reveal an inverse relationship between impedance and SOC. Additionally, the ECM parameters exhibit significant correlation with SOC, particularly in mid- to low-frequency regions. This research highlights that SOC profoundly influences ECM parameters, offering valuable insights into the performance of Li-ion batteries under various conditions.

A method for calculating the time‐varying equivalent circuit parameters of large‐capacity synchronous condenser considering field mutual leakage reactance

AbstractAccurate calculation of equivalent circuit parameters is a prerequisite for accurately calculating the large‐capacity synchronous condenser parameter model. Due to its special transient operating conditions, the high transient magnetic saturation effect during operation causes the non‐linearity and time‐varying of the equivalent circuit parameters. The field mutual leakage reactance is the critical factor affecting the field current, and the time‐varying of the equivalent circuit parameters is closely related to the field current. However, the existing equivalent circuit parameter calculation methods considering field leakage reactance cannot achieve time‐varying parameters. A calculation method of time‐varying equivalent circuit parameters based on a back propagation neural network algorithm is proposed, which solves the calculation problem of time‐varying equivalent circuit parameters considering field mutual leakage reactance. Then, a 300MVar condenser is taken as the research object, and the proposed method is used to simulate the different operating conditions of the condenser and verified by the finite element method and experiment. The results show that the method improves the calculation accuracy of the equivalent circuit parameter model, reduces the calculation time, and applies to different operating conditions.

Accelerating multilayer frequency selective surface absorber design by combining equivalent circuit models with machine learning

Designing high-performance electromagnetic functional materials and artificial structures is of great significance for electromagnetic wave modulation applications. Optimizing performance in the high-dimensional parameter space of electromagnetic functional materials has posed a challenging problem. This paper proposes the use of reinforcement and transfer learning methods to facilitate the quick and accurate design of wideband circuit analog absorbers (CAA). A trained reinforcement learning network is utilized to comprehend the relationship between reflectivity performance and changes in impedance parameter. Furthermore, the transfer learning method is applied to accelerate the training process, leading in a 20-fold reduction in the number of simulations. To validate the effectiveness of this approach, a double-layer absorber aiming for reflectivity less than −20 dB at 3–10 GHz is designed, requiring only 50 simulations. This demonstrates that the proposed method provides a flexible strategy for the interactive design of equivalent circuit and electromagnetic structural parameters. Moreover, it presents a novel and efficient solution for microwave absorber design, with potential applications across various microwave design fields.

A Taguchi method-based optimization algorithm for the analysis of the wind driven-self-excited induction generator

This paper investigates the use of a new global optimization algorithm that is based on Taguchi method to determine the performance parameters of self-excited induction generator being driven by variable speed wind. This analysis is based on solving equations obtained from the per-phase equivalent circuit of the induction generator. The equations have two unknowns namely the frequency and the magnetizing reactance. Both unknown are strongly dependent on the wind turbine speed, the capacity of the excitation, the load being connected at the terminals of the stator and eventually the per-phase equivalent circuit parameters. The resulting equations are nonlinear and subsequently to solve them one can employ either gradient-based algorithms or heuristic algorithms. This paper uses a new heuristic algorithm based on the Taguchi method which, in addition to its global research capability, offers superior characteristics in terms of accuracy and ease of implementation. A comparison with recently published optimization methods is carried out to show its performances in terms of accuracy and ease of implementation. The MATLAB software will be used to perform this analysis on a machine of 0.75 kW while some will be validated experimentally to confirm the aforementioned benefits.

Optimal Evaluation of Photovoltaic Cells Parameters Using Euclidean Distance Calculations

The relationship between current and voltage describes the features and characteristics of the photovoltaic (PV) cells. This relationship mainly depends on the equivalent circuit parameters of the PV cell model. Accurate estimation of these parameters is crucial for analyzing the performance of PV systems. This paper proposes a simple and efficient method to estimate the equivalent circuit parameters of the PV cells/modules. The main concept of the proposed method is to optimize the PV series resistance value using Euclidean distance calculations in such a way to get the corresponding best maximum power conditions. Various assessments have been employed in this paper to confirm the validity of the presented approach. Those include analyzing different commercial PV modules, experimental data, irradiance and temperature variations, and comparison with other reported algorithms. When compared with experimental data at standard test conditions, the mean absolute current and power differences are 0.0329 A and 0.6339 W, respectively. Furthermore, the mean absolute differences at normal operating cell temperature are 0.0120 A and 0.1412 W. The results have shown that the proposed method has confirmed its effectiveness in predicting the PV cell equivalent circuit characteristics for any PV cells/modules using only data available from the manufacturer’s datasheet.

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.

IMPROVEMENT OF THE METHOD OF CALCULATINGTHE PARAMETERS OF THE INDUCTION MOTORS REPLACEMENT SCHEME

The optimization of the equivalent circuit parameters of a three-phase induction motor with an equivalent double-circuit rotor is presented. The initial parameters of the equivalent circuit are estimated using a method known as engineering, based on the data provided in the manufacturer’s data sheet. The purpose of the work is aimed at increasing the accuracy of calculating currents and torques when using a double-circuit equivalent circuit of an induction motor by improving the method for determining the parameters of the equivalent circuit. A procedure for optimizing parameters has been developed to reduce errors between the calculated and actual values of the motor torque and current. Achieving the goal is ensured through the use of the author’s method of taking into account the nonlinearities of the motor, namely saturation of the magnetic circuit along the main path and scattering paths. To analyze the characteristics of an induction motor and predict its behavior in the event of faults and various operating modes, it is necessary to create a mathematical model of this motor. To ensure the adequacy of model calculations, it is necessary to take into account various nonlinearities of an induction motor, such as the effects of current displacement and machine saturation, steel losses, and others. The choice of a specific nonlinearity to take into account, as well as the methodology for taking it into account, are determined by the complexity of the tasks posed to the model. The depth of taking into account the nonlinear parameters of an induction motor depend on the requirements for the accuracy of the analysis and necessarily includes taking into account the most significant factors affecting the performance of the machine. A universal mathematical model has been created that describes an induction motor in a coordinate system that is stationary relative to the stator and takes into account the nonlinearity of its parameters. The parameters of the equivalent circuit of twelve industrial induction motors without and with optimization were assessed. A comparison was made of the results obtained from the engineering method and the actual data of the manufacturer to verify the effectiveness of the proposed method. Keywords: induction motor, nonlinearity of IM parameters, manufacturer’s data, optimization, parameter estimation, squirrel cage, mathematical modeling, experimental studies

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.