Power Electronic Circuits Research Articles

Investigation on composite materials use for EMI shielding in power electronics circuits

To ensure the reliability of embedded electronic systems, electromagnetic interferences (EMI) emitted from power electronic circuits must be limited. One possible solution would be to shield the power electronics circuits. In this paper, a shielding effectiveness study has been established in the time domain, above an AC/DC Flyback converter using composite materials. Obtained results have shown the positive impact of the composite materials regarding the mitigation of EMI emitted by power electronics circuits. Herein, this paper opens new horizons to simplify the EMC analysis of power electronic systems having enclosures shielded by composite materials.

A Review on Control Methods of SEPIC Converters

In recent years, electric vehicles have witnessed a surge in popularity due to their energy-saving and eco-friendly attributes. Unlike conventional internal combustion engine vehicles, electric vehicles exhibit superior performance and operational efficiency. Within the realm of modern electric vehicles, power electronic circuits, notably including DC-DC converters, play a pivotal role. Among these converters, single- ended primary-inductor converters (SEPIC) find extensive use in scenarios where minimizing input and output ripple currents is essential. The primary objective of this project is to conceive and put into action advanced controllers for SEPIC converters, catering to a diverse range of applications, encompassing battery-powered devices, solar energy systems, and LED lighting systems. Key Words: DC-DC converter, SEPIC converter, PID, SMC, ASMC, Fuzzy logic Control.

Global fast terminal sliding mode control with fixed switching frequency for voltage control of DC–DC buck converters

In this study, a global fast terminal sliding-mode control (GFTSMC), which offers a faster convergence performance than its counterparts is constructed for managing the state variables of the DC–DC buck converters. For the first time in this study, the GFTSMC was designed for power electronics circuits based on hysteresis modulation (HM). The HM technique’s variable switching frequency problem is overcome by reusing the GFTSMC structure, which enables the hysteresis band to be changed adaptively, and a fixed switching frequency is obtained. The proposed control scheme uses only one sensor for regulating the output voltage and controlling the switching frequency. Thus, an extremely economical and robust system, which is minimally affected by the negative aspects originating from the sensors, is obtained. Effectiveness of the proposed controller is validated with experimental studies. The experimental results shows that the output voltage and switching frequency are successfully controlled with good dynamic and steady state response. Finally, to validate the experimental feasibility of this paper, a comparison of the proposed method and four existing studies with different control schemes is presented.

Importance of low power electronic circuit design and its impact on energy consumption

<p class="MDPI16affiliation">In the modern world, Integrated Circuits (ICs) are an essential component of any electronic device, and it is practically impossible to imagine a world without them. When addressing energy consumption or environmental issues, many people, including researchers, tend to focus solely on power plants. However, today, there are billions of electronic devices, each containing numerous ICs, such as mobile phones, tablets, televisions, laptops, refrigerators, vacuum cleaners, cars, and more. In other words, a large portion of our modern energy consumption is attributed to electronic devices. Thus, reducing power consumption in each of these devices could significantly impact global energy consumption and environmental pollution. This paper emphasizes the importance of low-power Integrated Circuits and their potential to reduce worldwide energy consumption. It also briefly explores relevant technologies that contribute to energy efficiency in circuits, avoiding unnecessary complexities.</p>

Design of an Autonomous IoT Node Powered by a Perovskite-Based Wave Energy Converter

Abstract This paper presents the results of experimental research focused on wave energy harvesting and its conversion to power Internet of Things (IoT) devices. The harvesting and conversion process was performed using a wave energy converter (WEC) consisting of a lead zirconate titanate piezoelectric ceramic perovskite material and a prototype power electronic circuit. The designed WEC was considered as a power supply for an end node device (END) of an IoT network. The END consisted of a long-range radio module and an electronic paper display. A set of physical experiments were carried out, and the results confirmed that an energy surplus was supplied by WEC compared to the energy consumed by the END. Hence, the proposed scheme was experimentally validated as a convenient solution that could enable the autonomous operation of an IoT device. The use case presented here for the proposed WEC was analysed for selected sea areas on the basis of wave statistics. The novelty of this paper arises from an investigation that confirms that WECs can significantly contribute to the development of wireless and mobile IoT communication powered by freely available sea wave energy.

Junction Temperature Optical Sensing Techniques for Power Switching Semiconductors: A Review.

Recent advancements in power electronic switches provide effective control and operational stability of power grid systems. Junction temperature is a crucial parameter of power-switching semiconductor devices, which needs monitoring to facilitate reliable operation and thermal control of power electronics circuits and ensure reliable performance. Over the years, various junction temperature measurement techniques have been developed, engaging both non-optical and optical-based methods, highlighting their advancements and challenges. This review focuses on several optical sensing-based junction temperature measuring techniques used for power-switching devices such as metal-oxide-semiconductor field-effect transistors (MOSFETs) and insulated-gate bipolar transistors (IGBTs). A comprehensive summary of recent developments in infrared camera (IRC), thermal sensitive optical parameter (TSOP), and fiber Bragg grating (FBG) temperature sensing techniques is provided, shedding light on their merits and challenges while providing a few possible future solutions. In addition, calibration methods and remedies for obtaining accurate measurements are discussed, thus providing better insight and directions for future research.

Potential of Power Electronics to Improve the Power Quality of Network Grid

This study deals with voltage drop characterization of transmission systems by using power electronics circuits supplied from embedded generation. Many grid-connected power electronic systems, such as STATCOMS, UPFCs, and distributed generation system interfaces, use Voltage Source Inverters (VSI) connected to the supply network through a filter. This filter, typically a series inductance acts to reduce the switch harmonics entering the distribution network an alternative filter is an LCL network, which can achieve reduced levels of harmonic distortion at lower switching frequencies and with less inductance, and therefore has potential benefits for higher power application. However, systems incorporating LCL filters require more complex control strategies. This dissertation proposes a robust strategy for regulating the grid current connected via an LCL filter. The strategy integrates an outer loop grid current regulator with inner capacitor current regulation to stabilize the system. An asynchronous farm PI current regulation strategy is used for the outer grid current control loop. Linear analysis, simulation, and experimental results are used to verify the stability of the control algorithm across a range of operating conditions and finally, expressions for "harmonic impedance" of the system are derived to study the effects of supply voltage distortion on the harmonic performance of the system.

Fault Diagnosis of Power Electronic Circuits Based on Improved Particle Swarm Optimization Algorithm Neural Network

Fault Diagnosis of Power Electronic Circuits Based on Improved Particle Swarm Optimization Algorithm Neural Network

Design and validation of a multilevel voltage source inverter based on modular H-bridge cells

Generation, power conversion and subsequent integration of renewable energy generation systems, such as solar photovoltaic or wind, require an efficient power conversion system that can provide sufficient quality energy according to technical standards (e.g. IEEE 519–2022). In this context, this paper focuses on the analysis, design and experimental validation of a multilevel voltage source inverter (VSI) scheme based on H-bridge cells with a modular and scalable structure for its application in power electronic converter circuits. The designed and assembled experimental setup is a versatile platform for testing experimentally varied control strategies and power converter configurations, such as the number of levels (3, 5, 7 levels) and phases (single-phase or three-phase). Therefore, the hardware design process proposed for the H-bridge cell and the measurement and conditioning circuits for voltage and current signals necessary for implementing the control algorithms are explained in detail. Moreover, a quantitative analysis of the operation of the design was carried out from measurements made with the experimental platform to verify its correct operation. Among the analysed parameters, the generated harmonics level stands out, quantified by calculating the total harmonic distortion and the mean square error between the reference signals and the measured values.

An improved high-accuracy interpolation method for switching devices in EMT simulation programs

This paper presents an interpolation with Backward Euler (BE) method that enhances the switching simulations accuracy in an electromagnetic transient (EMT) simulation with a fixed time-step. Because of the switching operations on discrete instants, the simulations can show artificial voltage spikes and numerical oscillations (chatter), compromising the accuracy and producing misleading results. We thus present a method that eliminates the spurious switching losses and improves the accuracy by combining interpolation and extrapolation with a half-time-step BE solution over existing interpolation-based approaches to resolve the issues above. In addition, this improved method requires the same calculation steps as the industry-accepted instantaneous interpolation. Analytical discussion reinforced by the simulation studies for a simple and complex power electronic circuits demonstrates the accuracy and efficacy of the proposed interpolation with BE method.

A Comparative Performance Analysis of Wireless Power Transfer with Parametric Simulation Approach

This paper presents a parametric optimization and normalization approach for coreless Resonant Inductive Coupling Wireless Power Transfer (RIC-WPT) systems. The used system is based on a series–series (SS) compensated circuit via flat spiral coils. Moreover, the recommended approach system finds optimum capacitor values for the best efficiency point where the RIC-WPT system operates. Flat spiral three-dimensional (3D) coils are modelled and parametric analysed with different air gaps in ANSYS-Electronics-Maxwell software which is based on the Finite Element Method (FEM). Then power electronics circuit with a full-bridge inverter is designed in Ansys/Simplorer software. The coils and the power electronics circuit are co-simulated with parametric values. Thus, as a result of parametric simulation studies, the most efficient version of a Wireless Power Transfer (WPT) system structure is proposed with the design and normalized power electronics elements that can be physically applied for the chosen operating frequency value. As a result of the simulation studies, power transmission is realized with an efficiency of approximately 74.31% while the distance between the coils was 200 mm. Furthermore, useful information for WPT designs is been obtained thanks to co-simulation studies by changing power electronics circuit parameters and electromagnetic modelling parameters.

Overview of Signal Processing Problems in Power Electronic Control Circuits

This paper examines various aspects related to digital signal processing in digital control circuits used in power electronics. The discussion focuses on several common issues, including the sampling rate of signals (including phenomena such as aliasing and synchronization), coherent sampling, jitter of sampling pulses, sequential versus simultaneous sampling in multichannel systems, signal resolution (including signal-to-noise ratio, noise-shaping circuits, and changes in sampling speed), interpolation and decimation, and the conversion of analog circuits into digital form. One of the key contributions of this paper is the introduction of a new formula for calculating the resultant signal-to-noise ratio for three-stage digital control circuits. By carefully considering and correcting for sources of error, it is possible to increase the signal-to-noise ratio and minimize distortion components. This, in turn, leads to improved output/input current and voltage parameters, which can have a positive impact on the overall quality of energy processing in power electronic circuits.

Application of power electronic circuit design based on BP artificial neural network in environmental monitoring

Abstract Our natural resources have played an important role in building our economy. In addition to the number one energy resource, oil, electric energy is also the best quality and much in demand by society in the history of human civilization. It is because electrical energy can be fully developed and applied by society that the construction of human spiritual civilization has entered industrialization and high-tech information technology. The transmission and application of electric energy has been recognized by society, but how can we make it more reasonable and efficient for easy utilization. In order to solve the problem of how complex power electronic circuit devices can be more widely used with improved technology. This paper establishes the error estimation model of intelligent circuit from data collection and data prediction preprocessing, then proposes to optimize the number of nodes in the hidden layer by using particle swarm optimization algorithm to address the limitations of the traditional BP neural network, and uses the optimized number of nodes in the hidden layer to build a BP neural network structure to train the training sample data, and calculates the error data of the intelligent circuit based on the trained BP neural network to test the sample data. The method established in this paper is used to perform the evaluation of intelligent circuit operation errors. The simulation example shows that the established model can effectively evaluate the smart circuit operation error, and the evaluation accuracy is significantly improved compared with the traditional evaluation method.

Modeling Methodology Based on Fast and Refined Neural Networks for Non-Isolated DC–DC Converters With Configurable Parameter Settings

Compared with conventional physics-based methods, e.g., analytical modeling and numerical modeling, data-driven methods can extract input-to-output relationships from the data without much prior knowledge of the physical system, thus showing great potential in modeling power electronics (PE) converters with complex switching behaviors and configurable parameter settings. Previous data-driven PE circuit modeling approaches are mostly based on sequential neural networks, and their execution speed suffers from large sequential lengths due to a high sampling rate for high modeling accuracy. Moreover, modeling of refined singular ripples is missing and configurable parameter settings are not available in these data-driven modeling approaches. To address the above-mentioned issues, this paper proposes a hybrid physics-informed machine learning (ML) method to model the non-isolated DC-DC converters. The approach empirically decomposes the output signals into transient large signals and periodic small signals. For transient large signals, a fully-connected neural network (NN) is used to map circuit parameters with system characteristics, such that configurable circuit parameter settings are allowed. For periodic signals, a long short-time memory (LSTM) network together with convolutional neural network (CNN) is used to accelerate the simulation by predicting signal features in the compressed latent space. A buck converter with configurable parameter settings is modeled by the proposed hybrid physics-informed ML method. Periodic ripples are successfully generated, while execution speed is about 10 times faster than that of conventional numerical methods.

Increasing PEM fuel cell performance via fuzzy-logic controlled cascaded DC-DC boost converter

The voltage level produced by Proton Exchange Membrane (PEM) fuel cell (FC), which is one of the clean energy sources, is low for many industrial applications. For this reason, for many industrial applications such as electric vehicles, it is necessary to use a boost type DC-DC power electronic circuit at the output of PEM FC. In this case, in addition to the PEM FC performance, the dynamic performance and efficiency of the DC-DC converter to be used affect the performance and efficiency of the total system. In this study, a single-switch cascaded DC-DC boost converter, which has both higher voltage gain and more efficiency compared to conventional cascade converter and other boost type converters, is proposed for PEM FC. Since the proposed single-switch cascaded DC-DC boost converter includes only one controlled-switch, it is efficient as well as smaller in size and less costly compared to the other types. In addition, the proposed single-switch cascaded DC-DC boost converter is tested with the traditional PID and fuzzy-logic control methods to observe the dynamic performance of PEM FC. When the fuzzy logic controller is compared with the PID controller, it is clearly seen that it gives 21% more successful results as per rise time, 71% settling time, 97% overshoot, and 26% RMSE (Root Mean Square Error) error rate. As a result, when the proposed single-switch cascaded DC-DC boost converter is regulated via fuzzy control method, a more efficient PEM FC system which has better dynamic performance can be designed.

Shifting of Nonlinear Phenomenon in the Boost converter Using Aquila Optimizer

Power electronics circuits are characterized by nonlinear dynamics, because of the cyclic switching between a finite number of topologies, which can give rise to a variety of behaviors. DC/DC converters are prone to nonlinear phenomena, such as bifurcations, quasi-periodic and chaotic responses, which can make it difficult or even impossible to analyze, predict, and control the converter's behavior. This paper offers an examination of the chaotic behavior of the DC/DC boost converter and suggests an optimized PID controller as solution to the nonlinear phenomena. Aquila optimizer AO is employed to determine the ideal parameters for the controller by computing the discrepancy between the reference current and the value of the inductor current, as well as the discrepancy between the inductor current readings during switch openings. The simulation results using MATLAB demonstrate the effectiveness of the proposed solution.
 

Artificial intelligence based switching frequency regulation with fast terminal sliding mode control for DC–DC step-down converters

Making the best voltage/current regulation against disturbances and uncertainties and, most importantly, to minimize chattering effect in power electronics circuits, the hysteresis modulation based (HM) sliding mode control (SMC) is widely used. There are various research on this subject in the literature. However, the variable switching frequency that HM-SMC brought about has regrettably overlooked in the majority of these research. This problem is addressed in depth in this paper by demonstrating how the switching frequency is affected by various factors. Next, the fuzzy logic control (FLC) is proposed for the first time as a solution for switching frequency regulation in a power electronics circuit. The proposed FLC for switching frequency regulation fortifies the system described in this study and sets it apart from many other HM-SMC studies in the literature with its advantages against the difficulties caused by variable switching frequency such as excessive switching and driver power losses. On the other hand, the fast terminal SMC (FTSMC) which has significantly superior convergence performance than its counterparts, has been recommended for voltage regulation. The proposed FTSMC technique employs only one voltage sensor different from the past literature. This simplifies the proposed control mechanism in practical implementation and also makes the system economical. The two proposed controllers’ compatibility with one another has been tested through experimental tests, including the steady-state condition, variations in switching frequency reference value, step change of load resistance, output voltage reference value variation, and finally step change of input voltage. The outcomes of the experiments demonstrate that the switching frequency and output voltage are successfully regulated with good dynamic and steady state performance. Finally, the proposed techniques have been compared with six recent approaches from the existing literature to highlight their performance.

The Output Voltage Estimation of Power Transformer Integrated with a Three Phase T-Type Inverter

The issues related to integrating these systems into the grids continue to gain importance with the increasing use and importance of renewable energy sources. Therefore, the importance of power distribution transformers is increasing. Besides, these power distribution transformers are connected to the grid with power electronics circuits and inverters. Considering the modular inverter structures, ease of maintenance, and connection, three-level T-type inverters are chosen for this study. The secondary output voltage of the power transformer is estimated by using circuit parameters such as the dead time of the inverter circuit, PWM switching frequency, and modulation rate. Based on the finite element analysis analysis according to the selected parameters, 810 data are obtained with time-dependent parametric analysis. The adaptive neuro-fuzzy inference system model is constructed by considering the simulation data to estimate the secondary output of the power transformer of these parameters. In the training phase of the model, 648 randomly selected data from 810 data obtained by ANSYS-Electronics/Simplorer are used. The remaining 162 data are used in the testing process to measure system performance. As a result of the analysis made by ANFIS, the Root Mean Square Error (RMSE) error is found as 2.475%. Since the values obtained in the estimation process of the study are very close to the simulation values, the ANFIS method can be used as an estimation method that will give accurate results during the design phase.

Transmission of Power and Signal Multiplex for Electric Vehicles Using Cascaded Multilevel Inverters

Abstract: P&SMT, or power and signal multiplex transmission, is a method for transmitting communication signals using power electronic circuits. A three-phase cascaded multilevel inverter-based P&S MT system is recommended in this investigation. By allowing communication signals to be transmitted without utilizing a Controller Area Network bus, the proposed solution can lower the wiring expense of the existing electric vehicle (EV) communication system. The system's architecture enables battery balancing discharge and motor speed management for EVs. In a simulation system proposed in MATLAB/Simulink, both power and communication signals are effectively conveyed using the combined pulse width modulation scheme and frequency shift keying approach. The maximum signal rate of the proposed system is established at 600 bits per second by analyzing the bit error rate of the sent signal.

A New Modified Non-Approximative Method for Dynamic Systems Direct Calculation

This scientific paper presents a novel modified non-approximative method for instantaneously calculating state variables in a compact form. The method provides a direct solution in the discrete time domain, allowing for the specification of state variable values at any discrete time instant without requiring knowledge of previous variable values. This approach is useful for estimating voltage and current stresses of semiconductor elements and circulating energy within power electronic circuits, which is crucial for the correct design and operation of such systems. The paper utilized the z-transform with a long repetitive period to accelerate the calculation time and applies a method to solve the Steinmetz circuit using Matlab. The paper includes detailed simulations and a comparison of time consumption using both Euler implicit and the proposed direct non-approximative methods. Theoretical and simulation results were validated using Matlab/Simulink circuit simulator, demonstrating the effectiveness and efficiency of the proposed method.