Inductive Load Research Articles

Performance Analysis of Three Phase Cascaded H-Bridge Multilevel Inverter Design for Solar Power Plant Optimization

An inverter is an electrical device that converts direct current (DC) into alternating current (AC). Typically, a standard inverter operates at three voltage levels: +Vdc, -Vdc, and 0. However, a multilevel inverter consists of several smaller inverters connected in a series to produce multiple voltage levels at the output. The primary advantage of this type of inverter lies in its ability to produce a much lower harmonic distortion compared to traditional, non-multilevel inverters. Additionally, the switching components of a multilevel inverter operate at lower frequencies, which makes it more suitable for highpower applications. This research focuses on a threephase cascaded multilevel inverter, specifically generating output waveforms with up to seven levels. The study involves conducting experiments using RL loads, to observe how these variations affect the output waveforms and their harmonic distortions. The result, THDi values are much lower, with the 3rd harmonic contributing 0.02%, the 5th contributing 0.006%, the 7th contributing 0.004%, the 9th contributing 0.002%, the 11th contributing 0.002%, and the 13th harmonic contributing just 0.001%. These results suggest that the voltage harmonic more significant harmonic distortion than the current, particularly at the 13th harmonic order. This increase highlights the effect of inductive loads on the performance of the inverter, particularly in terms of harmonic content. These findings are crucial for optimizing multilevel inverters in practical applications, ensuring improved performance and efficiency.

Study of thermohydrodynamic processes in the air environment in the system of melting ice on the wires of the power transmission line

The paper considers issues related to modeling thermal and hydrodynamic processes in the "wire – ice shell – air" system that occur during melting of ice on wires. The problem of ice shell growth on the surface of power transmission line wires has been known for a long time, and many works in the field of ice growth control and technical means of combating this phenomenon are devoted to its solution. Recently, works have appeared on melting systems that operate without disconnecting lines from consumers, which increases the reliability and uninterruptible power supply, reduces economic losses from undersupply of products during power supply interruptions. The process of ice melting can occur under conditions of heating the conductors with a high current to a steady positive temperature until the ice shell is destroyed. In this case, switching to the melting mode is carried out for a short period of time. An alternative to this method is to combine power supply to consumers and ice melting. In this case, the heat generation capacity in the wires is less, the melting time is increased, but there is no need to disconnect consumers. The problem of maintaining the line in the operating mode of transmitting electric energy to consumers is solved by additionally loading the line with reactive currents by connecting a certain inductive load. The increase in currents and power coming from the supply transformer to the line must be technically feasible so as not to overload the source and not cause its shutdown. Due to power limitations, it is necessary to carry out accurate calculations of thermal processes to determine acceptable modes of melting the ice layer. Complex modeling of thermohydrodynamic processes in the "wire – ice shell – air" system is considered. Several methods for determining the coefficients of convective heat exchange at the boundaries of the conductor at different wind speeds are considered.

Interrelation of Gate Resistance and Emitter/Source Inductance Impact on Inductive Load Phase-Leg Crosstalk

Interrelation of Gate Resistance and Emitter/Source Inductance Impact on Inductive Load Phase-Leg Crosstalk

Grid-Forming Fuel Cell System for an Islanded AC Grid

This paper proposes a two-stage converter that can black start an isolated AC Microgrid with a Fuel Cell (FC) as the primary energy source. The first stage is connected to the FC and employs a Three-Leg Interleaved Boost DC/DC Converter (IBC), while the second is a Three-Phase Voltage Source Converter (VSC). The DC/DC stage utilizes a Cascade Voltage Control (CVC) to mitigate voltage fluctuations in the DC-link caused by the variability of the FC voltage. For the DC/AC stage, three distinct grid-forming (GFM) strategies are implemented with two of them with multi-loop cascaded structure and one with a single-loop structure. The power circuit of the system is simulated using the Real-Time Simulator (RTS) HIL 602+ from Typhoon-HIL, with the control strategies embedded on the Digital Signal Processor (DSP) TMS320F28379D - F28379D LaunchPad from Texas Instruments (TI). The performance of the cases are verified through CHIL simulations for a balanced and unbalanced inductive load steps. The results demonstrate that for both tests the GFM single loop structure presents smoother transients and shorter recovery times. Additionally, for the unbalanced loads, all the cases present similar results for the DC variables with more pronounced differences at the AC side.

Portable Arbitrary Pulse Generator for Driving Microcoils for Micromagnetic Neurostimulation

Micromagnetic stimulation (μMS) is a promising branch of neurostimulation but without some of the drawbacks of electrical stimulation. Microcoil (μcoil)-based magnetic stimulation uses small micrometer-sized coils that generate a time-varying magnetic field, which, as per Faraday’s Laws of Electromagnetic Induction, induces an electric field on a conductive surface. This method of stimulation has the advantage of not requiring electrical contact with the tissue; however, these μcoils are not easy to operate. Large currents are required to generate the required magnetic field. These large currents are too large for standard test equipment to provide, and additional power amplifiers are needed. To aid in the testing and development of micromagnetic stimulation devices, we have created a compact single-unit test setup for driving these devices called the µCoil Driver. This unit is designed to drive small inductive loads up to ±8 V at 5 A and 10 kHz.

Cxcl10 is protective during mouse-adapted SARS-CoV-2 infection.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of the coronavirus disease 2019 (COVID-19) pandemic, remains endemic worldwide. Circulating levels of the chemokine CXCL10 are strongly positively associated with poor outcome; however, its precise role in SARS-CoV-2 pathogenesis and its suitability as a therapeutic target have remained undefined. Here, we challenged mice genetically deficient in Cxcl10 with a mouse-adapted strain of SARS-CoV-2. Infected male, but not female, Cxcl10-/- mice displayed increased mortality compared to wild type controls. Histopathological damage, inflammatory gene induction and virus load in the lungs of male mice were not broadly influenced by Cxcl10 deficiency. However, accumulation of B and T lymphocytes in the lung parenchyma of infected mice was reduced in the absence of Cxcl10. Thus, during acute SARS-CoV-2 infection, Cxcl10 regulates lymphocyte infiltration in lung and confers protection against mortality. Our preclinical model results do not support targeting CXCL10 therapeutically in severe COVID-19.

Advanced hybrid control for induction motor combining ANN-PID speed controller with neural predictive current regulator based on particle swarm optimization

This paper presents a hybrid control strategy for an induction motor (IM) organized into two nested loops. In the outer loop, an adaptive artificial neural network-based proportional-integral-derivative (ANN-PID) controller is used for speed control. The ANN-PID is divided into two stages: the first stage includes an adaptive ANN speed estimator, and the second stage includes an adaptation algorithm that fine-tunes both the weights and biases of the ANN estimator and the parameters of the PID controller. In the internal loop, a predictive current controller is used to control IM currents using neural networks. Specifically, the neural predictive controller (NPC) approaches the control problem by presenting it as an optimization problem using a neural predictor for IM currents. The considered objective function includes two elements: the current tracking error and the electromagnetic torque ripple. This function is computed over a given time horizon informed by predictions of IM currents. The particle swarm optimization (PSO) algorithm is applied to determine the optimal solution for this optimization task. The effectiveness of the hybrid control scheme is demonstrated by simulation results obtained using Matlab/Simulink, highlighting its superiority over conventional control methods. The proposed hybrid control is characterized by a reduction in torque ripple and overshoot, while also showing robustness to variations in load, rotor resistance, and rotor inductance. Comparisons with an ANN controller and a fuzzy PI controller further demonstrate the superior performance of the hybrid controller in handling nonlinear dynamics and maintaining control accuracy under various operating scenarios.

Correlation-based polarity-check algorithm for instrument transformers

A polarity identification is very important for operation of transformers, measurement and protection equipment, where it is useful in analyzing of transformer connections and operation as well as testing of protective systems. Moreover, it’s essential in assessment of power systems performance during both normal and abnormal operation. Ensuring the correct polarity of the primary and secondary windings in voltage and current transformers is of paramount importance for various measurement and protection schemes in power networks. This paper proposes a digital polarity detector and tester using correlation coefficients and nine polarity indices calculated for instrument transformer signals. In order to test the performance of the proposed polarity tester algorithm, MATLAB code is imported to the LABVIEW model, and the numerical data obtained from the synchronous generator terminals via instrument transformers are interfaced with the computer through the Data Acquisition Card (DAC). The experimental system consists of a motor-generator set supplying a three-phase inductive load with instrument transformers connected to measure each phase voltage and current. The obtained results for various operating conditions and different types of abnormal conditions prove that the suggested algorithm is accurate, reliable and applicable to smart grids and substation automation systems. It can be considered as an integrated system incorporated with digital fault recorders, relays and meters.

An Optimized Multi-Level Control Method for Wireless Power Transfer System Using the Particle Swarm Optimization Algorithm

A Wireless Power Transfer (WPT) system, known for its contactless power delivery, is extensively used for power supply in spacecraft applications. Achieving efficient and stable power transfer necessitates the integration of DC/DC converters on both the primary and secondary sides of WPT systems for power conversion and control. Traditional efficiency optimization methods primarily focus on impedance matching within the wireless power resonance network, often neglecting the overall efficiency optimization of multi-stage DC-DC and WPT systems. This oversight results in suboptimal overall system efficiency despite optimal efficiency in the wireless transmission segment. Additionally, the time-varying nature of mutual inductance and load parameters during power transmission in WPT systems presents challenges for maximum efficiency tracking and power control. This paper introduces a multi-level coordinated control efficiency optimization method for WPT systems utilizing the particle swarm optimization (PSO) algorithm. This method takes into account the transmission losses across all power conversion units within the WPT system, establishing a mathematical model for the joint optimization of overall system transmission efficiency and power. The PSO algorithm is then employed to solve this optimization model using estimated mutual inductance and load values. By adjusting the DC/DC converters on both sides, the method ensures optimal overall system efficiency and consistent power transmission. Experimental results indicate that under varying load and mutual inductance conditions, a Series–Series (SS) compensated WPT system using this method achieves a 200 W power output with maximum efficiency tracking, a power output error of 0.63%, and an average transmission efficiency of 86.2%. This demonstrates superior power transmission stability and higher efficiency compared to traditional impedance matching methods.

A Decoupled Modulation Strategy for Constant Voltage/Current Wireless Charging System Under High Coils Misalignment

ABSTRACTOutput fluctuation and lower transmission efficiency under load and mutual inductance variation are hot concerned in the wireless charging system for power batteries. In this paper, a decoupled tracking strategy is proposed to realize constant voltage (CV) or current (CC) output and high transmission efficiency. The circuit model of series–series compensation network is built, and corresponding transmission characteristics can be derived. First, the load and mutual inductance value can be estimated by measuring the primary electrical information, including the inverter output voltage, current, and the phase error between them. Then load‐independent voltage or current output characteristics under coils misalignment can be maintained by tracking the optimal switching frequency of inverter part. In addition, the value of output voltage or current can be adjusted flexibly for different operation occasions by the employment of pulse‐width modulation. As a result, the load‐independent output characteristics realization and output adjustment can be decoupled. Based on only the primary measuring information, the CV/CC output can be maintained via the proposed hybrid control strategy when the coils misalignment and load variation happen, increasing the robustness of whole wireless power transfer (WPT) system. Furthermore, the soft switching of all power switches in the inverter part can be realized to reduce the switching loss. Compared with previous research, the proposed wireless charging system has a higher power density and a simplified control strategy. Finally, an experimental platform with 60‐V charging voltage and 3.6‐A charging current is built to verify the feasibility of the proposed sys‐tem and control method.

Investigating the Effects of Induction Heating on a Submerged Hollow Cylindrical Element

ABSTRACTThis article proposes an induction heating element that addresses heat transfer and thermal homogenization while being fully submerged in a liquid, specifically focusing on heating of water as a case study. The design calculations, fabrication, and realization of a resonant induction heating system that heats the proposed heating element are presented. The geometric shape of proposed heating element is a hollow cylinder that maintains structural strength while delivering required thermal energy because of an external time‐varying magnetic field. Detailed mathematical modeling of the proposed heating element's equivalent electric circuit has been presented while considering physical parameters including diameter, thickness, height, material properties, magnetic field frequency, and skin effect. A laboratory scale prototype of the induction heating system including the proposed heating element has been built, and experiments have been demonstrated. The experimental results of the working induction heating resonant inverter and RLC resonant circuit inductance and capacitance with induction load are presented. Additionally, the results of thermographic images and temperature–time profile of the water sample, which was heated using the proposed heating element, are provided to demonstrate the heating element's reliability and practicality. This research contributes to the field of induction heating technology by investigating a heating element that is submerged in a liquid medium, resulting in a uniform temperature distribution throughout the liquid. The conventional method of heating water in a stainless steel cup‐shaped container is an inefficient heat transfer process. In stainless steel cup‐shaped containers, a portion of the energy input used to boil the water is lost to the environment through the surface area of the container that is not in direct contact with the water. This heat loss occurs due to the container's design, which exposes a large surface area to the surrounding environment, allowing thermal energy to dissipate through conduction, convection, and radiation.

Cxcl10 is required for survival during SARS-CoV-2 infection in mice.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of the coronavirus disease 2019 (COVID-19) pandemic, remains endemic worldwide ~5 years since the first documented case. Severe COVID-19 is widely considered to be caused by a dysregulated immune response to SARS-CoV-2 within the respiratory tract. Circulating levels of the chemokine CXCL10 are strongly positively associated with poor outcome; however, its precise role in pathogenesis and its suitability as a therapeutic target have remained undefined. Here, we challenged 4-6 month old C57BL/6 mice genetically deficient in Cxcl10 with a mouse-adapted strain of SARS-CoV-2. Infected male, but not female, Cxcl10 -/- mice displayed increased mortality compared to wild type controls. Histopathological damage, inflammatory gene induction and virus load in the lungs of male mice 4 days post infection and before death were not broadly influenced by Cxcl10 deficiency. However, accumulation of B cells and both CD4+ and CD8+ T cells in the lung parenchyma of infected mice was reduced in the absence of Cxcl10. Thus, during acute SARS-CoV-2 infection, Cxcl10 regulates lymphocyte infiltration in the lung and confers protection against mortality. Our preclinical model results do not support targeting CXCL10 therapeutically in severe COVID-19.

Analysis of Reactive Power Flow in an Electric Power System

Optimal power flow analysis is a calculation to minimize an objective function, namely generation costs or transmission losses by regulating the active power and reactive power generation of each interconnected power system generator by taking into account certain limits. The growth of industrial loads which are dominated by inductive loads requires a fairly large reactive power supply. This reactive power requirement will of course reduce the available power that can be transmitted to the load. Reactive power flow in transmission lines will reduce the active power distribution capacity required by the load. Reactive power flow that is too large can also cause losses. However, this reactive power is also an important component in the stability of the electric power system. For this reason, the flow of active and reactive power in transmission lines needs to be regulated so that the capacity and stability of the electric power transmission system is maintained.

Reliability Enhancement of a Double-Switch Single-Ended Primary Inductance–Buck Regulator in a Wind-Driven Permanent Magnet Synchronous Generator Using a Double-Band Hysteresis Current Controller

The wind power exchange system (WECS) covered in this paper consists of a voltage source inverter (VSI), a DSSB regulator, and an uncontrolled rectifier. An AC grid or a heavy inductive or resistive load (RL) can be supplied by this system. The DSSB is a recently developed DC-DC regulator consisting of an improved single-ended primary inductance regulator (SEPIC) followed by a buck regulator. It has a peak efficiency of 95–98% and a voltage gain of (D (1+D)/(1−D). where D is the regulator transistor’s on-to-off switching ratio. The proposed regulator improves the voltage stability and MPPT strategy (optimal or maximum power-point tracking). The combination of the DSSB and the proposed regulator improves the efficiency of the system and increases the power output of the wind turbine by reducing the harmonics of the system voltages and current. This method also reduces the influence of air density as well as wind speed variations on the MPPT strategy. Classical proportional–integral (PI) controllers are used in conjunction with a vector-controlled voltage source inverter, which adheres to the suggested DSSB regulator, to control the PMSM speed and d-q axis currents and to correct for current error. In addition to the vector-controlled voltage source inverter (which follows the recommended DSSB regulator), classical proportional–integral controllers are used to regulate the PMSM speed and d-q axis currents, and to correct current errors. In addition, a model Predictive Controller (PPC) is used with the pitch angle control (PAC) of WECS. This is done to show how well the proposed WECS (WECS with DSSB regulator) enhances voltage stability. A software-based simulation (MATLAB/Simulink) evaluates the results for ideal and unoptimized parameters of the WT and WECS under a variety of conditions. The results of the simulation show an increase in MPPT precision and output power performance.

The Development of a Novel Transient Signal Analysis: A Wavelet Transform Approach

This paper presents a new method for the analysis of transient signals in the frequency domain based on the Continuous Wavelet Transform (CWT). The proposed case study involves test signals measured from an electronic switch considering open and close operations. The source is connected to inductive, resistive, and capacitive loads. Resonance behaviors are introduced and compared with the Discrete Fourier Transform (DFT). Multiple factors, such as reliability, repeatability, high noise attenuation, and the smoothing of the analyzed spectrum, are considered in this study. This proposed study highlights the effectiveness of CWT in signal processing, especially in obtaining a detailed spectrum that reveals the behavior of electrical circuits. Resonance behaviors were analyzed, demonstrating that the signal processing performed by CWT is better for spectrum analysis than DFT. This study shows the potential of CWT to analyze transient electrical signals, specifically for identifying and characterizing the behavior of load connections and disconnections.

Fuzzy Modelling Algorithms and Parallel Distributed Compensation for Coupled Electromechanical Systems

Modelling and controlling an electrical Power Generation System (PGS), which consists of an Internal Combustion Engine (ICE) linked to an electric generator, poses a significant challenge due to various factors. These include the non-linear characteristics of the system’s components, thermal effects, mechanical vibrations, electrical noise, and the dynamic and transient impacts of electrical loads. In this study, we introduce a fuzzy modelling identification approach utilizing the Takagi–Sugeno (T–S) structure, wherein model and control parameters are optimized. This methodology circumvents the need for deriving a mathematical model through energy balance considerations involving thermodynamics and the non-linear representation of the electric generator. Initially, a non-linear mathematical model for the electrical power system is obtained through the fuzzy c-means algorithm, which handles both premises and consequents in state space, utilizing input–output experimental data. Subsequently, the Particle Swarm Algorithm (PSO) is employed for optimizing the fuzzy parameter m of the c-means algorithm during the modelling phase. Additionally, in the design of the Parallel Distributed Compensation Controller (PDC), the optimization of parameters pertaining to the poles of the closed-loop response is conducted also by using the PSO method. Ultimately, numerical simulations are conducted, adjusting the power consumption of an inductive load.

Productivity enhancement of continuous miners packages of underground mines with energy conservation in industrial sectors

Energy auditing is crucial for both emerging and developed nations, focusing on aspects such as energy efficiency, quality and intensity. This becomes especially significant in the industrial sector, where major operating costs involve materials, machinery, personnel and energy. A key objective is identifying energy consumption in the Continuous Miner Machine, boasting a 1050 KW connected load, to explore opportunities for energy savings and improved quality. The execution of an energy audit promises increased efficiency, enhanced power quality, reduced costs and prevention of energy wastage. This research study has meticulously examined the electrical equipment supplying power to Continuous Miner Machines, proposing modifications to boost production through energy-efficient methods. Comprehensive assessments of primary substations, including Incomers, Transformers, Feeders, etc., involve tests for voltage, current, power factor, harmonics and AC waveform. Thermal imaging is employed to analyze the operational temperature of the electrical equipment. The graphical representations of test outcomes have highlighted a significant recommendation: installing an Automatic Power Factor Controller on the inductive load side of transformers could lead to a notable 3.85% reduction in energy costs.

A Novel Linear-Based Closed-Loop Control and Analysis of Solid-State Transformer

In this paper, a new linear-based closed-loop control method for a Solid-State Transformer (SST) has been proposed. In this new control method, individual current and voltage loops for each of the power conversion stages (AC-DC, DC-DC, DC-AC) are implemented. The feedback between the input and output control signals for each loop is achieved through the voltage on the DC link capacitors and the current transferred between the converters. This enables the SST to be controlled easily in a linear-based closed-loop manner without the need for complex computations. In order to evaluate the performance analysis of the proposed control system, a simulation of an SST with approximately 10 kVA apparent power was performed. Based on the obtained simulation results, the response time of the proposed control method for dynamic load variations was proved to be in the range of 40 milliseconds, and it has been observed that this method allows electrical power to be transferred from the load to the grid. The power factor value of SST under inductive load is measured to be approximately 99%, and the overall system efficiency is 96% and above, indicating that this proposed new control method has very high performance.

Coordinated Control of Constant Output Voltage and Maximum Efficiency in Wireless Power Transfer Systems

This article presents a coordinated control method used for wireless power transfer (WPT) systems. This method can improve WPT system transmission efficiency while maintaining the constant output voltage. First, the topology of the DC–DC converter is selected and the equivalent circuit model of the WPT system is established. Then, the WPT system characteristics are discussed and the mutual inductance estimation process is presented. Furthermore, the coordinated control method is proposed, where the constant voltage output is achieved by connecting the Buck–Boost converter after the diode rectifier. Meanwhile, the optimal phase shift angle is calculated and sent to the controller to achieve maximum transmission efficiency tracking control, according to the measured load voltage and current. Finally, simulations and experiments are adopted to verify the proposed coordinated control method. The experimental results indicate that the average system transmission efficiency is increased by 1.80% and the efficiency fluctuation is decreased by 2.67% when the system load resistance varies, while the average system transmission efficiency is increased by 1.80%, and the efficiency fluctuation is decreased by 3.14% when the mutual inductance changes. This means the proposed coordinated control method is effective under the conditions of the WPT load and mutual inductance variations.

A Deep Reinforcement Learning Approach to DC-DC Power Electronic Converter Control with Practical Considerations

In recent years, there has been a growing interest in using model-free deep reinforcement learning (DRL)-based controllers as an alternative approach to improve the dynamic behavior, efficiency, and other aspects of DC–DC power electronic converters, which are traditionally controlled based on small signal models. These conventional controllers often fail to self-adapt to various uncertainties and disturbances. This paper presents a design methodology using proximal policy optimization (PPO), a widely recognized and efficient DRL algorithm, to make near-optimal decisions for real buck converters operating in both continuous conduction mode (CCM) and discontinuous conduction mode (DCM) while handling resistive and inductive loads. Challenges associated with delays in real-time systems are identified. Key innovations include a chattering-reduction reward function, engineering of input features, and optimization of neural network architecture, which improve voltage regulation, ensure smoother operation, and optimize the computational cost of the neural network. The experimental and simulation results demonstrate the robustness and efficiency of the controller in real scenarios. The findings are believed to make significant contributions to the application of DRL controllers in real-time scenarios, providing guidelines and a starting point for designing controllers using the same method in this or other power electronic converter topologies.