Equivalent Circuit Parameters Research Articles

Automatic Identification Algorithm of Equivalent Electrochemical Circuit Based on Electroscopic Impedance Data for a Lead Acid Battery

Obtaining tools to analyze and predict the performance of batteries is a non-trivial challenge because it involves non-destructive evaluation procedures. At the research level, the development of sensors to allow cell-level monitoring is an innovative path, and electrochemical impedance spectrometry (EIS) has been identified as one of the most promising tools, as is the generation of advanced multivariable models that integrate environmental and internal-battery information. In this article, we describe an algorithm that automatically identifies a battery-equivalent electrochemical model based on electroscopic impedance data. This algorithm allows in operando monitoring of variations in the equivalent circuit parameters that will be used to further estimate variations in the state of health (SoH) and state of charge (SoC) of the battery based on a correlation with experimental aging data corresponding to states of failure or degradation. In the current work, the authors propose a two-step parameter identification algorithm. The first consists of a rough differential evolution algorithm-based identification. The second is based on the Nelder–Mead Simplex search method, which gives a fine parameter estimation. These algorithm results were compared with those of the commercially available Z-view, an equivalent circuit tool estimation that requires expert human input.

Кодовое управление параметрическими моделями индукционных нагревателей

In this paper, we describe our approach to building controllable models of induction heaters. Parameters of equivalent circuits of aluminum heating inductors include certain components tied to secondary elements. As long as metal properties are subject to change during the heating process, resistive and reactive parts of equivalent circuits should be taken into account. Adjustable resistive components have rarely been used in circuit models. To control equivalent resistive two-terminal parts, we offer pulse code control of impedance-changing switches. Controlling switching time in models with series, parallel, and mixed connection provides required softness of resistive conductivity change. Control characteristics of current and voltage were obtained with use of a simulator. As the result of our numerical experiment, the set of operating parameters for an induction device was determined.

Implementation of Boost PFC in the Induction Heating System for EMI–RFI Suppression

The present work deals with the design and performance analysis of high frequency resonant inverter based Induction Heating (IH) System employing Boost Power Factor Correction (PFC) technique to overcome the problems due to EMI and RFI. Most of the existing techniques use passive filters for harmonics attenuation that fails to meet the present day requirement because of drawbacks like considerably high THD, poor dynamic performance, etc. This paper presents a new control approach for boost PFC based on inner and outer loops to eliminate the problems due to harmonics in the IH system. The equivalent circuit parameter model of the IH system has been used to analyze the presence of harmonics and the incorporation of boost PFC at the input of the system shows its elimination as per the stringent EMI-RFI regulations. Moreover, attention has been paid off to the design algorithm of the boost PFC and a detailed mathematical analysis has been done to outline an approach for its parameter selection. A comparative analysis of the IH system with and without the incorporation of the boost PFC has been done in terms of the THD in the input current waveform. The findings of the present work show that the incorporation of Boost PFC eliminates the harmonics in the IH system in a better manner than the existing techniques. Doi: 10.28991/HIJ-2021-02-02-05 Full Text: PDF

Opposition-based equilibrium optimizer algorithm for identification of equivalent circuit parameters of various photovoltaic models

Opposition-based equilibrium optimizer algorithm for identification of equivalent circuit parameters of various photovoltaic models

The decreasing of the influence of parasitic inductance of tested object on the accuracy of its electrical capacitance measurement

This paper gives a description of measurement technique which can be used in practice of carrying out estimation of electrical capacitance of tested object with substantial stray inductance. Electrical capacitance is determined as a ratio of mean value of discharge current to the mean value of time derivative, taken from voltage on unknown capacitance. The decreasing of deleterious impact of stray inductance on accuracy of measurements is achieved by proper selection of the duration of analyzed signals. In proposed technique the duration is limited by instants of time that correspond to the maximum value of discharge current and to the termination of transient. The accuracy of described method for electrical capacitance estimation is affected by noisy components of obtained oscillograms. This deleterious impact can be alleviated by smoothing of time dependence by applying of least square method. Another reason for lost of accuracy is associated with possible influence of skin-effect in conductive elements of discharge circuit, which can cause time dependence of resistance and inner inductance of conductive parts of tested object and discharge circuit. Described technique, however, is based on taking into consideration independent on time parameters of equivalent lamped discharge circuit. Nevertheless, the example of practical implementation has shown that described approach allows to partially mitigate the influence of stray inductance on carried out measurements of electrical capacitance, as the value of relative error turned out to be equal to 2.04%

Transparent ultra-wideband double-resonance-layer metamaterial absorber designed by a semiempirical optimization method.

In this study, a transparent ultra-wideband double-resonance-layer absorber was designed using a semiempirical optimization method. In this method, an equivalent circuit model, genetic algorithm, and parameter fitting are employed to reduce the computation time and improve the design flexibility. Simulations and measurements show that the as-designed absorber can achieve ultrawide microwave absorption in the range of 2.00 to 11.37 GHz with a fractional bandwidth of 140.2%. Furthermore, electric field and surface current distributions show that the broad bandwidth was derived from the good matching of the absorption peaks in the two resonance layers. In addition, the target waveband of the as-designed absorber covered the wavebands of WiFi and radio-frequency identification, as well as part of the 5G waveband. This makes the proposed absorber a good candidate for daily electromagnetic pollution reduction.

Experimental Determination of Equivalent Iron Loss Resistance for Prediction of Iron Losses in a Switched Reluctance Machine

Switched reluctance machine (SRM) has progressed as a suitable contender in the family of electrical machines for its high starting torque and better performance in different operating conditions. The need for accurate modeling of this machine is, therefore, dependent on the accurate determination of losses of which iron loss is exigent. This article aims to determine iron loss from the equivalent circuit parameters of the machine based on the input data tables that are directly obtained from the experiments carried out on an existing four-phase, bifilar wound SRM. The procedure and necessary steps for the loss separation method are well defined and supported by the theoretical and practical results. The experimental determination of the iron losses has been compared with the predicted results under the same operating conditions.

Synchronous Machine Winding Modeling Method Based on Broadband Characteristics

The accurate establishment of the equivalent circuit model of the synchronous machine windings’ broadband characteristics is the basis for the study of high-frequency machine problems, such as winding fault diagnosis and electromagnetic interference prediction. Therefore, this paper proposes a modeling method for synchronous machine winding based on broadband characteristics. Firstly, the single-phase high-frequency lumped parameter circuit model of synchronous machine winding is introduced, then the broadband characteristics of the port are analyzed by using the state space model, and then the equivalent circuit parameters are identified by using an optimization algorithm combined with the measured broadband impedance characteristics of port. Finally, experimental verification and comparison experiments are carried out on a 5-kW synchronous machine. The experimental results show that the proposed modeling method identifies the impedance curve of the circuit parameters with a high degree of agreement with the measured impedance curve, which indicates that the modeling method is feasible. In addition, the comparative experimental results show that, compared with the engineering exploratory calculation method, the proposed parameter identification method has stronger adaptability to the measured data and a certain robustness. Compared with the black box model, the parameters of the proposed model have a certain physical meaning, and the agreement with the actual impedance characteristic curve is higher than that of the black box model.

An Accurate Neural Network-Based Consistent Gate Charge Model for GaN HEMTs by Refining Intrinsic Capacitances

Neural network-based capacitance models are accurate, but some of them are not charge-conservative. In this work, a novel consistent gate charge model for GaN high electron mobility transistors is presented based on neural networks. The equivalent circuit parameters are extracted using the multiobjective gray wolf optimizer-based hybrid method, which improves the accuracy of parameter extraction. To obtain more reliable data sets for accurate neural network-based modeling, the outliers in the extracted intrinsic capacitances are automatically detected and removed using the isolation forest technique. The gate charge is obtained by integrating the capacitances with the voltages at different temperatures. A neural network is used to model the bias- and temperature-dependent gate charges, and the intrinsic capacitance formulation is obtained by taking the partial derivative of the gate charge function with respect to the voltages. The proposed model is charge-conservative and requires no transcapacitances. The large-signal model is implemented in the Advanced Design System and verified by small- and large-signal measurements. Good agreement is obtained between the measurements and simulations.

Optimal Parameter Estimation Methodology of Solid Oxide Fuel Cell Using Modern Optimization

An optimal parameter estimation methodology of solid oxide fuel cell (SOFC) using modern optimization is proposed in this paper. An equilibrium optimizer (EO) has been used to identify the unidentified parameters of the SOFC equivalent circuit with the assistance of experimental results. This is presented via formulating the modeling process as an optimization problem considering the sum mean squared error (SMSE) between the observed and computed voltages as the target. Two modes of the SOFC-based model are investigated under variable operating conditions, namely, the steady-state and the dynamic-state based models. The proposed EO results are compared to those obtained via the Archimedes optimization algorithm (AOA), Heap-based optimizer (HBO), Seagull Optimization Algorithm (SOA), Student Psychology Based Optimization Algorithm (SPBO), Marine predator algorithm (MPA), Manta ray foraging optimization (MRFO), and comprehensive learning dynamic multi-swarm marine predators algorithm. The minimum fitness function at the steady-state model is obtained via the proposed EO with value of 1.5527 × 10−6 at 1173 K. In the dynamic based model, the minimum SMSE is 1.0406. The obtained results confirmed the reliability and superiority of the proposed EO in constructing a reliable model of SOFC.

Parameter identification of pulsed eddy current testing equivalent circuit model and its application to defect evaluation

The equivalent circuit model of pulsed eddy current testing (PECT) has simple mathematics but its applications are limited to qualitative analysis such as principle illustration and signal interpretation. In this paper, the parameters of equivalent circuit model are estimated using system identification method and quantitative relationships are found between some of the parameters and the size of the defect. The equivalent circuit equations were solved from the perspective of system analysis to yield the system transfer function. An m-sequence of 10 order was selected to excite the system and the probe current was used as the output. A set of experiment input-output data for system identification were obtained by performing experiments on two aluminium alloy 6061 slabs, one of which was machined with five slots of different widths, and the other one was machined with five depth-varied slots. The equivalent circuit parameters were finally estimated based on the identified transfer function parameters. It is found that the values of resistance and self-inductance of the secondary windings decrease greatly and monotonically with the increase of the slot width or depth. The self-inductance is more sensitive to the slot size variation than the resistance. Both of them have the potential to serve as the signal feature for defect evaluation in PECT applications.

Genetic Algorithm & Fuzzy Logic-based Condition Monitoring of Induction Motor Through Estimated Motor Losses

ABSTRACT In this paper, a novel approach for condition and performance monitoring of induction motor through estimated motor losses is proposed and explained. The novelty in the proposed approach is minimal non-intrusive measurements and does not require disconnection of motors from the load. In many systems, the losses measured directly or indirectly in a motor are of the lump sum in nature. The main advantage of the system prescribed in this paper gives losses in the segregated form, which is directly used to assess the internal condition of the motor. This approach will assess the condition of induction motors for internal faults such as stator faults, rotor faults, core faults, bearings faults, etc. The equivalent circuit parameters and motor losses are estimated using the developed Genetic Algorithm (GA). The estimated motor loss data are compared with the NEMA & IE Standards and if any deviation found will be reported as faults. The reported information is linked to the developed fuzzy algorithm to identify the faults exactly along with its severity level. The proposed approach was tested and evaluated with the help of LT motors ranging from 5 to 200 HP in real-time from a selected industry.

Use of equivalent circuit analysis and Cole-Cole model in evaluation of bioreactor operating conditions for biomass monitoring by impedance spectroscopy.

The most important parameter in bioprocesses is biomass, where not only the quantity produced in a culture but also the behavior that is presented are important concerns. It is clear that conditions of operation in a bioreactor affect biomass production, but how operation conditions affect the measurement of biomass on-line is of special interest. We studied the effect of bioreactor operating condition variations on model parameters using impedance spectroscopy for biomass monitoring. The model parameters analyzed were capacitance, resistance, alpha (α), conductivity delta (∆σ) and critical frequency (fc). These model parameters were obtained by fitting data from impedance measurements to an equivalent circuit model and Cole-Cole conductivity model. The effect of operating conditions on the medium with no cells was estimated by the percentage of change in each model parameter. The operating conditions with the most significant percentage of change were determined, by comparing to the percentage of change of the same model parameters obtained, during a fermentation of Bacillus thuringiensis as a cellular model. Equivalent circuit parameters were mainly affected by variation in pH, temperature and aeration, whereas Cole-Cole parameters were affected by variation in agitation, aeration, temperature and pH. Therefore, any variation in these operating conditions (within the test interval) during a fermentation may generate changes in monitoring parameters, which will not be a direct consequence of any change in the properties of the biomass.

Design, implementation and speed estimation of three-phase 2 kW out-runner permanent magnet BLDC motor for ultralight electric vehicles

Brushless DC motor has specifications such as high efficiency, high startup moment and silent running. Thanks to its low inertia, high torque/size and power/size ratio, it can be used in specially designed vehicles such as electric vehicles (EVs), spacecraft and submarines. As there is no brush and commutator that in its structure can cause arc forming, it can be used in fire-sensitive areas. In this study, a 2 kW three-phase out-runner permanent magnet brushless DC (BLDC) motor was designed to be used in ultralight EV. The size of the motor, the magnetic equivalent circuit and the electrical equivalent circuit parameters required for the BLDC motor design process were analytically calculated. The finite element method was then used to evaluate flux density, flux distributions, torque and motor efficiency and was approved for analytical design. The BLDC motor, which has about 89% efficiency, has been manufactured and mounted on an ultralight EV. Finally, the motor speed was estimated using a new robust hybrid metaheuristic model called artificial neural networks (ANNs) trained with particle swarm optimization (PSO) and radial movement optimization (RMO). A genuine and unconventional technique was used to examine the model's performance. That is, using three distinct input variables such as output torque, efficiency and output power, the output variable of motor speed was estimated. And then, the results were compared using the other three hybrid models. In all performs, it was seen that ANNs trained with PSO + RMO model achieved the most successful results with the lowest errors.

Transformer Model Identification by Ārtap

The paper presents how Ārtap can be used for determining the equivalent circuit parameters of a one phase transformer as a benchmark problem. The following unknown parameters of the equivalent circuit are identified: primary resistance and primary leakage reactance, secondary resistance and secondary leakage reactance, finally magnetizing resistance, and magnetizing reactance. The known quantities from measurement are the primary voltage, primary current, power factor, secondary voltage, and the load resistance. Algorithms implemented in Ārtap are used for determining the transformer parameters and the results are compared with the analytical solution.

Qualitative and Quantitative Analysis of Different Inductance Measurement Techniques for IPM Synchronous Machines

The accurate estimation of equivalent circuit parameters (EEC) is necessary for performance analysis and control of electric drives using the analytical models of electrical machines. The analytical models of PM motor assume constant values of d and q axis inductances. Since the B vs. H curve of the lamination material is non-linear, the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$L_{d}$</tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$L_{q}$</tex-math></inline-formula> inductances vary as the stator current increases. So, the assumption of constant inductances results in an erroneous prediction of the motor’s behavior. Hence, an accurate estimation of nonlinear variation of inductances in PM motors is necessary. There are many techniques specified in standards and literature for the evaluation of IPM machine inductances. However, a reliable method to capture the nonlinear variation of inductances is not discussed. This work gives a comparative analysis of various inductance measurement techniques for the interior permanent magnet (IPM) machines to capture the nonlinear variation of inductances with current based on motor performance. Statistical and qualitative analysis of experimental and FEA results on an IPM motor design is done in this work to determine a reliable inductance measurement technique.

Elicitation of Scattering Parameters of Dual-halo Dual-dielectric Triple-material Surrounding Gate (DH-DD-TM-SG) MOSFET for Microwave Frequency Applications

This paper presents an analytical model for intrinsic short-circuit admittance (Y) parameters of DH-DD-TM-SG MOSFET. Y parameters have been modeled using different small-signal equivalent circuit parameter which is used to find the Scattering parameters. These Y parameters have further been employed for computing S-parameters. These parameters are further used to investigate the microwave performance parameters of the proposed device. The Unilateral Power Gain and the maximum oscillation frequency is determined to evaluatethe microwave performance. The proposed device shows a higher cut-off frequency (f_T) and maximum oscillation frequency as to TM-SG MOSFET. The proposed device exhibits a 4.2% improvement in U_T 2.81% in G_ms and 6.9% improvement in G_MTPG as compared to TMSG. The analytical result of DH-DD-TM-SG MOSFET is in accordance with the simulated results.

Bayesian estimation of equivalent circuit parameters of photovoltaic cells

The equivalent circuit model of a photovoltaic cell is useful for understanding device loss mechanisms as well as the design and analysis of systems using photovoltaic cells. Although nonlinear least-squares methods are routinely applied for the extraction of equivalent circuit parameters using current–voltage characteristic curves, they only yield a point estimation sensitive to the initial value and do not provide an estimation error. In this study, a data-driven approach using Bayesian estimation is proposed to extract equivalent circuit parameters. Contrary to the conventional least-squares method, this method does not require tedious initial value adjustments and provides an estimation error.

A Ka-band pattern-reconfigurable microstrip antenna enabled by PIN diodes with accurate extraction of equivalent circuit parameters

A Ka-band microstrip antenna based on PIN diodes with accurate extraction of equivalent circuit parameters for pattern reconfigurability is proposed in this work. With the increase in operation frequency, the parasitic effect introduced by PIN diodes has tremendous influence on the performance of reconfigurable antennas; hence, the conventional equivalent circuit parameters of the PIN diodes are not applicable for higher-frequency applications, such as millimeter-wave circuits and antennas. Therefore, accurate equivalent circuit models of the conventional PIN diodes are essential in the millimeter-wave reconfigurable antenna design. Based on the combination of simulation and experimental results, accurate equivalent circuit model parameters for the millimeter-wave range of the PIN diode are extracted, with a pattern-reconfigurable antenna being developed afterwards. The proposed antenna consists of two PIN diodes, two interdigital capacitors, an L-shaped slot, and their bias networks. Particularly, the interdigital capacitors are utilized to isolate direct current (DC) from radio frequency circuits, which is able to improve the economic efficiency of the antenna notably as compared with conventional chip capacitors in the Ka-band. By combining a suitable arrangement of the diodes’ location and the DC bias networks, the main beam direction of the proposed antenna can be switched between −60° and 60°. To demonstrate the proposed idea, a prototype antenna is fabricated and measured. The measured results agree with the simulation quite well, with a good performance around 30 GHz and a gain greater than 5 dBi for both modes being achieved.

Modelling of Supercapacitors Based on Simplified Equivalent Circuit

The need for energy storage devices especially in renewable energy applications has increased the use of supercapacitors. Accordingly, several supercapacitor models have been proposed in previous researches. Nevertheless, most of them require an intensive test to obtain the model parameters. These may not be suitable for an initial simulation study, where a simple model based on the datasheet is required to evaluate the system performance before building the hardware prototype. A simplified electrical circuit model for a supercapacitor (SC) based on the voltage-current equation is proposed in this paper to address this issue. This model doesn’t need an intensive test for accuracy. The structural simplicity and decent modelling accuracy make the equivalent electrical circuit model very suitable for power electronic applications and real-time energy management simulations. The parameters of the proposed model can be obtained from the datasheets value with a minimum test requirement. The experimental method to provide the parameters of the supercapacitor equivalent circuit is described. Based on the proposed method, the supercapacitor model is built in Matlab/Simulink, and the characteristics of equivalent series resistance (ESR) measurement and cycle life are compared with datasheets. The simulation results have verified that the proposed model can be applied to simulate the behaviour of the supercapacitor in most energy and power applications for a short time of energy storage. A supercapacitor test circuit is given to test the charge and discharge of supercapacitor modules. The experimental results are suitable for simulation results.