Design Of Power Electronic Systems Research Articles

Investigation of the Trapping and Detrapping Behavior by the On-State Resistance at Low Off-State Drain Bias in Schottky p-GaN Gate HEMTs

GaN power HEMTs enable the design of power electronic systems with highest efficiencies and reduced size. Despite strong advancements in device reliability, charge carrier trapping is still an important challenge. The applied methodology allows to characterize defects that cause the dynamic RDS,on in GaN power devices at product level with flexibility in duty cycle, number of pulses and mission profile. A pronounced trapping is observed for lateral GaN-on-Si HEMTs with Schottky p-GaN gate structure at low drain bias and long off-state pulses (> 100 ms). The effect is investigated by fast determination of the on-state resistance RDS,on under different trap capturing conditions: a) different drain bias b) off-state time and number of cycles c) variation of temperature. The trapping and detrapping effects are characterized and the activation energy is extracted from time constants. An elevated on-state resistance was present for up to 3 hours. The threshold voltage modification due to high drain bias does explain the significant RDS,on increase.

Brain-inspired methods for achieving robust computation in heterogeneous mixed-signal neuromorphic processing systems

Abstract Neuromorphic processing systems implementing spiking neural networks with mixed signal analog/digital electronic circuits and/or memristive devices represent a promising technology for edge computing applications that require low power, low latency, and that cannot connect to the cloud for off-line processing, either due to lack of connectivity or for privacy concerns. However, these circuits are typically noisy and imprecise, because they are affected by device-to-device variability, and operate with extremely small currents. So achieving reliable computation and high accuracy following this approach is still an open challenge that has hampered progress on the one hand and limited widespread adoption of this technology on the other. By construction, these hardware processing systems have many constraints that are biologically plausible, such as heterogeneity and non-negativity of parameters. More and more evidence is showing that applying such constraints to artificial neural networks, including those used in artificial intelligence, promotes robustness in learning and improves their reliability. Here we delve even more into neuroscience and present network-level brain-inspired strategies that further improve reliability and robustness in these neuromorphic systems: we quantify, with chip measurements, to what extent population averaging is effective in reducing variability in neural responses, we demonstrate experimentally how the neural coding strategies of cortical models allow silicon neurons to produce reliable signal representations, and show how to robustly implement essential computational primitives, such as selective amplification, signal restoration, working memory, and relational networks, exploiting such strategies. We argue that these strategies can be instrumental for guiding the design of robust and reliable ultra-low power electronic neural processing systems implemented using noisy and imprecise computing substrates such as subthreshold neuromorphic circuits and emerging memory technologies.

An Overview of Complex Instability Behaviors Induced by Nonlinearity of Power Electronic Systems with Memristive Load

The proposal of the memristor, considered as the fourth basic circuit element, suggests a new possibility for the design of high-performance power electronic systems. However, it also brings new challenges. At present, more and more electrical equipment and systems have demonstrated that their external characteristics can exhibit “8”-shaped hysteresis loops and can be regard as memristive equipment and systems. In order to satisfy the requirements of controllability, flexibility, efficiently, and so on, most memristive equipment and systems are not directly connected to the power grid but instead obtain their own required powering through various forms of power electronic converters. Note that memristive loads are distinctive and demonstrate unique nonlinear behaviors. Similarly, there can be nonlinearity from the resistor (R), inductor (L), or capacitor (C) load, but there is no combination of only R, L, and C that could produce memristive characteristics. In particular, the memristance of memristive devices changes continuously during the operation process; in addition, practical power electronic systems composed of memristive devices and power supplies have strong nonlinear characteristics, which are more likely to result in various complex behaviors and are not conducive to the stable operation of the systems. Therefore, exploring complex instability behaviors of power electronic systems with strong nonlinearity in depth is necessary for better protection and utilization of memristive devices. This paper provides an outline of the status of research on complex behaviors of power electronic systems with memristive load; it is expected to provide guidance for the study of complex behavior of strongly nonlinear systems.

Real-Time FPGA Simulation of High-Voltage Silicon Carbide MOSFETs

This article presents a real-time field-programmable gate array (FPGA)-based dynamic model of high-voltage and high-current silicon carbide (SiC) metal-oxide-semiconductor field-effect transistor ( <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">mosfet</small> ) half-bridge power modules. The dynamic switching model utilizes the Shichman and Hodges equations using voltage-dependent nonlinear device capacitances and module electrical parameters to obtain an accurate dynamic model of the device switching transients. The key device states gate-source voltage, drain current, and drain-source voltage are modeled and discretized using forward Euler discrete integration method. Analysis of synthesizing the discrete-time model into real-time FPGA-based system with real-time data output from the on-board digital-to-analog converter is presented in detail. The model is utilized in modeling a 320-kW, medium-voltage dc/dc dual-active bridge converter and verified using dynamic experimental results from a 3.3-kV SiC <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">mosfet</small> half-bridge power module. It has been shown that the presented discrete-time dynamic switching model accurately describes the turn- <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</small> and turn- <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off</small> switching transients of the SiC power module at various voltage and current levels. Such models are useful for rapid and cost effective design and prototyping of SiC-based power electronic systems by defining key design and operating parameters, such as deadtime, switching frequency, and switching losses.

A Sampling Optimized Method for Frequency Response Measurement in Power Electronics Systems

Frequency response measurement plays a crucial role in the design, analysis, and debugging of power electronics systems. However, traditional measurement methods, including the sweep method and the adaptive frequency injection method, have some problems in ease of use, stability, accuracy, and data inheritance. To address these problems, this article establishes a sampling optimized method based on the idea of global optimization by placing each measurement point in the interval with the largest estimated measurement error in the corresponding measurement cycle, so as to achieve a rapid reduction of the total measurement error. Compared with traditional methods, this method is easy to use, highly stable, and has higher accuracy than traditional methods, and its good data inheritance also allows users to incrementally add new points after the measurement is completed to further improve the accuracy. In addition, the importance of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Uniqueness of Search Path</i> is also revealed in this article. The effectiveness of the proposed method is demonstrated through extensive numerical tests and experiments.

Artificial Intelligence Techniques: How Can it Solve Problems in Power Electronics?: An Advancing Frontier

Artificial intelligence (AI) techniques have recently emerged as the powerful and advancing frontier in power electronics and their impact in the next generation of power electronics appears to be tremendous. The advent of AI has brought a challenge to the engineers specialized in power electronics which is already a complex, interdisciplinary and fast-moving technology. The AI provides very powerful tools for design, simulation, control, estimation, fault diagnostics, and fault-tolerant control of power electronic systems, which are particularly important in modern smart grid and renewable energy systems (RESs) in addition to its applications in traditional power electronics and motor drives area. A smart or intelligent grid is basically an advanced electric power grid of tomorrow using state-of-the-art technologies in power electronics, power systems, computers, communications, information, AI and cyber that will improve the system availability, reliability, power quality, energy efficiency, and security with optimum resource utilization and economical electricity to the consumers.

Additive Manufactured Impinging Coolant, Low Electromagnetic Interference, and Nonmetallic Heat Spreader: Design and Optimization

Abstract With the increase of electronic device power density, thermal management and reliability are increasingly critical in the design of power electronic systems. First, increased density challenges the capability of conventional heat sinks to adequately dissipate heat. Second, higher frequency switching in high voltage, high current, wide bandgap power modules is creating intensified electromagnetic interference (EMI) challenges, in which metallic heat removal systems will couple and create damaging current ringing. Furthermore, mobile power systems require lightweight heat removal methods that satisfy the heat loads dissipated during operation. In this effort, we introduce an additive manufacturing (AM) pathway to produce custom heat removal systems using nonmetallic materials, which take advantage of impinging fluid heat transfer to enable efficient thermal management. Herein, we leverage the precision of additive manufacturing techniques in the development of three-dimensional optimized flow channels for achieving enhanced effective convective heat transfer coefficients. The experimental performance of convective heat removal due to liquid impingement is compared with conventional heat sinks, with the requirement of simulating the heat transfer needed by a high voltage inverter. The implementation of nonmetallic materials manufacturing is aimed to reduce electromagnetic interference in a low weight and reduced cost package, making it useful for mobile power electronics.

An Automated Semi–symbolic State Equation Generation Method for Simulation of Power Electronic Systems

Computer-aided analysis is playing an important role in the design and control of power electronic systems. A discrete-state event-driven (DSED) framework with state-space modeling has been proposed recently for accurate and efficient off-line simulation. Nevertheless, automated equation formulation for arbitrary circuits is also required to develop the DSED framework toward general simulation software. However, the traditional state equation generation method is very time-consuming, especially for large-scale systems due to the variable topologies brought by switching events. In this article, an automated semi-symbolic state equation generation method is proposed. Based on the switching function modeling of basic switching legs, an explicit function from switching states to state equation matrices is given, which reduces the computational cost without sacrificing any accuracy. The operating and topological characteristics of power electronics systems are utilized for further optimization. The proposed method greatly increases the simulation efficiency of power electronic systems, especially for large-scale systems. Two cases of the 2 MW 4-port solid-state transformers with different system scales are simulated with the proposed method under the DSED framework. About 700-fold and 1200-fold acceleration is achieved compared with one fast-speed commercial software, where the proposed method contributes 50-fold and 110-fold acceleration in the two cases, respectively.

A Breakthrough in Design Verification of Megawatt Power Electronic Systems

Design verification of megawatt power electronic systems has long been plagued by lack of simulation tools that can handle a system with hundreds of switching devices and over different time scales. The task is even more challenging if we want to verify large and small-signal dynamic performances and device switching behaviors simultaneously [1]. A recent breakthrough allows design simulation of such a complex system simulation to run up to 1,000 times faster, over vastly different time scales (ns vs. ms) and with unprecedented accuracy (<1% error) and virtually free of convergence problems. The discrete-state event driven (DSED) approach [3], supported by the piecewise analytical transient (PAT) model [4], has demonstrated its capability of simulating such a complex system with record speed of a few seconds or a few minutes and free of convergence problems. The capability will move the virtual prototyping of megawatt power electronic systems one step closer to reality. Specific performance metrics will be presented in the article, together with case studies. The DSED and PAT techniques, currently available for practicing engineers through the commercial software DSIM [5], will usher in a new era in megawatt power electronic system design and design verification. The DSED technique and its benefits are equally applicable throughout the industry.

Measurement of Power Dissipation Due to Parasitic Capacitances of Power MOSFETs

Analysis of the switching losses in a power MOSFET is crucial for the design of efficient power electronic systems. Currently, the state-of-the-art technique is based on measured drain current and drain-to-source voltage during the switching intervals. However, this technique does not separate the switching power due to the resistance of the MOSFET channel and due to the parasitic capacitances. In this paper, we propose a measurement method to extract the power dissipation due to the parasitic capacitances of a MOSFET, providing useful information for device selection and for the design of efficient power electronic systems. The proposed method is demonstrated on a basic boost converter. The proposed method shows that the existing method underestimates the turn-On losses by 41% and overestimates the turn-Off losses by 35%.

Variable switching frequency hybrid PWM technique for switching loss reduction in a three-phase two-level voltage source inverter

Power loss reduction is one of the main objectives in power electronic system design for achieving higher efficiencies and enhancing system reliability. In this regard, this paper aims to develop a variable switching frequency hybrid pulse width modulation (VSF-HPWM) method to maximize loss saving while maintaining the same current total harmonic distortion (THD) of the conventional scheme. In doing so, this technique utilizes the modulation signal and the switching frequency simultaneously. Using a predefined mathematical representation of current ripple in every switching cycle, the modulating signal (either discontinuous or conventional space vector modulation) with lower RMS current ripple is applied. Meanwhile, the number of commutations under the constrains of constant RMS ripple is reduced by varying the switching frequency. The performance analysis is validated through MATLAB Simulink which shows that the proposed strategy can save up to 53% of switching losses with a similar THD of the conventional scheme.

Artificial Intelligence Aided Automated Design for Reliability of Power Electronic Systems

This paper proposes a new methodology for automated design of power electronic systems realized through the use of artificial intelligence. Existing approaches do not consider the system's reliability as a performance metric or are limited to reliability evaluation for a certain fixed set of design parameters. The method proposed in this paper establishes a functional relationship between design parameters and reliability metrics, and uses them as the basis for optimal design. The first step in this new framework is to create a nonparametric surrogate model of the power converter that can quickly map the variables characterizing the operating conditions (e.g., ambient temperature and irradiation) and design parameters (e.g., switching frequency and dc link voltage) into variables characterizing the thermal stress of a converter (e.g., mean temperature and temperature variation of its devices). This step can be carried out by training a dedicated artificial neural network (ANN) either on experimental or simulation data. The resulting network is named as $\text{ANN}_{1}$ and can be deployed as an accurate surrogate converter model. This model can then be used to quickly map the yearly mission profile into a thermal stress profile of any selected device for a large set of design parameter values. The resulting data is then used to train $\text{ANN}_{2}$ , which becomes an overall system representation that explicitly maps the design parameters into a yearly lifetime consumption. To verify the proposed methodology, $\text{ANN}_{2}$ is deployed in conjunction with the standard converter design tools on an exemplary grid-connected PV converter case study. This study showed how to find the optimal balance between the reliability and output filter size in the system with respect to several design constraints. This paper is also accompanied by a comprehensive dataset that was used for training the ANNs.

Piecewise Analytical Transient Model for Power Switching Device Commutation Unit

Taking switching transients of switching devices into consideration in design and simulation of power electronic systems has long been a huge obstacle. Sufficient accuracy has to be ensured, meanwhile more significantly the transient model has to be practical, i.e., providing a convergent result with an acceptable solving speed and a convenient parameter extraction technique. Aiming at both targets, this paper proposes a piecewise analytical transient (PAT) model for switching device commutation unit, taking an IGBT-p-i-n diode pair as an example. A piecewise time-varying voltage source-current source pair is utilized to model the IGBT-p-i-n diode pair. With sufficient accuracy, PAT modeling methodology noticeably increases the solving speed and improves the convergence of converter simulations. Model expressions and datasheet-driven parameter extractions are illustrated in detail. Experimental and simulated results are presented and compared to validate both the accuracy and the practicability of the proposed PAT model, expected to be employed in transient simulations of power electronic systems.

Robust Stability Analysis of a DC/DC Buck Converter Under Multiple Parametric Uncertainties

Stability studies are a crucial part of the design of power electronic systems, especially for safety critical applications. Standard methods can guarantee stability under nominal conditions but do not take into account the multiple uncertainties that are inherent in the physical system or in the system model. These uncertainties, if unaccounted for, may lead to highly optimistic or even erroneous stability margins. The structured singular value-based $\mu$ method justifiably takes into account all possible uncertainties in the system. However, the application of the $\mu$ method to power electronic systems with multiple uncertainties is not widely discussed in the literature. This paper presents practical approaches to applying the $\mu$ method in the robust stability analysis of such uncertain systems. Further, it reveals the significant impact of various types of parametric uncertainties on the reliability of stability assessments of power electronic systems. This is achieved by examining the robust stability margin of the dc/dc buck converter system, when it is subject to variations in system load, line resistance, operating temperature, and uncertainties in the system model. The $\mu$ predictions are supported by time-domain simulation and experimental results.

Identification Estimated with Bat Search Algorithms for Modeling of Inverter System

The grid interlinked type inverter is a device that can efficiently transmit electricity through the conversion of power electronic systems. It would be advantageous to make use of various forms of renewable energy when considering the transmission of electric power. The prediction based on numerical simulations will be helpful in the development for the understanding and design of power electronic systems, predictive controller, power flow, stability, power quality analysis of the grid interlinked type inverter. This paper seeks to present a new technique examining the grid interlinked type inverter when creating a model of a nonlinear system identification through the use of nonlinear autoregressive exogenous inputs - wavelet neural network (NLARX-WNN). The NLARX-WNN was able to demonstrate the modeling approach needed for a single phase grid interlinked type microhydropower inverter. In addition, the model has estimated the optimal set of parameters via the bat search algorithms (BA). The tests of microhydro electric type inverter is performed and its model is defined. The simulated results made the NLARX-WNN solution, which was estimated with the BA, capable of the proposed scheme and this may serve to improve the accuracy of estimation when assessing the behaviour of the single phase grid interlinked type inverter. Once completed, the mathematical model can represent the system for analysing and identifying the characteristics of an electrical power system.

Fault-Tolerant Power Electronic System for Drag Power Kites

An approach for a fault-tolerant power electronic system for drag power kites is proposed. The key idea is to use a high number of electrical cables in the tether and leave rotor drivetrains in groups isolated on the kite, in the tether, and on the ground. The power flow is paralleled behind an uninterruptible power supply of each drivetrain group on the ground. It is shown that this approach hardly affects the overall system performance, for example, due to the anyways high optimal number of electrical cables in the tether. With this approach, a fault in one drivetrain group does only affect the same drivetrain group and a fault between two drivetrain groups affects only the same two drivetrain groups. A fuse system and a fault shut-off control for the power converters are proposed, with which also faults between two drivetrain groups lead at most to unavailability of only one drivetrain group. In particular also open circuit faults and short circuit faults in the tether are mitigated and are overall not harmful for the system and a usual multicopter-like landing is still possible. Therefore, the proposed power electronic system design has no single point of failure. A generalization and a number of variants are discussed. In detail, a number of power electronic topologies and both tether power transmission types, DC and AC, are possible. The proposed approach was verified by a high number of circuit simulations and by a proof-of-principle demonstrator. In all cases it was confirmed that any open circuit fault and any short circuit fault lead at the most to unavailability of only one rotor drivetrain group.

Digital Signal Processing in Power Electronics Control Circuits, Second Edition [Book News

This textbook has been revised and extended for its second edition (the first edition was published in 2013). It discusses problems related to the design and implementation of digital control algorithms for power electronics systems using the digital signal processing (DSP) approach. The contents of the book are organized into seven chapters: 1) “Introduction” 2) “Analog Signals Conditioning and Discretization” 3) “Selected Methods of Signal Filtration and Separation and Their Implementation” 4) “Selected Simulation Methods and Programs for Power Electronic Circuits” 5) “Selected Active Power Filter Control Algorithms” 6) “Digital Signal Processing Circuits for Digital Class-D Power Amplifier” 7) “Conclusion and Future Work.” The book opens in Chapter 2 with a discussion on the processing of analog-to-digital (A/D) signals and the most common source of errors. The author presents an overview of A/D converters suitable for power electronics control. Digital filters, multirate circuits, digital filter banks, and microcontrollers for power electronics are discussed in Chapter 3. This second edition includes a new and useful Chapter 4 that presents problems pertaining to the simulation of digitally controlled power electronic systems and includes numerous program listings in MATLAB and PSIM. The next two chapters include descriptions of selected active power filter (Chapter 5) and class-D power amplifier control algorithms (Chapter 6) as well as their implementation, simulation, and experimental results. The book concludes with a summary and a midterm forecast for future research and developments. The contents of the book are easy to read and presented in an interesting way with good illustrations. Each chapter includes an extensive list of references. This book fills a gap between power electronics and digital signal processing. I strongly recommend it to engineering educators, graduate students, and industry engineers who are interested in understanding the design of modern DSP-controlled power electronic systems.

A Lumped Thermal Model Including Thermal Coupling and Thermal Boundary Conditions for High-Power IGBT Modules

Detailed thermal dynamics of high-power IGBT modules are important information for the reliability analysis and thermal design of power electronic systems. However, the existing thermal models have their limits to correctly predict these complicated thermal behavior in the IGBTs: The typically used thermal model based on one-dimensional RC lumps have limits to provide temperature distributions inside the device; moreover, some variable factors in the real-field applications like the cooling and heating conditions of the converter cannot be adapted. On the other hand, the more advanced three-dimensional (3-D) thermal models based on finite-element method (FEM) need massive computations, which make the long-term thermal dynamics difficult to calculate. In this paper, a new lumped 3-D thermal model is proposed, which can be easily characterized from FEM simulations and can acquire the critical thermal distribution under long-term studies. Meanwhile, the boundary conditions for the thermal analysis are modeled and included, which can be adapted to different real-field applications of power electronic converters. Finally, the accuracy of the proposed thermal model is verified by FEM simulations and experimental results show a good agreement.

Energy Efficiency Improvement via Bus Voltage Control of Inverter for Electric Vehicles

Although great effort has been devoted with various approaches on the improvement in energy efficiency of electric vehicles, much of the focus has been on the design of electric devices and power electronic systems and of energy storage systems with energy management strategies. This paper proposes a bus voltage control method that actively and dynamically controls the bus voltage applied to the inverter through a dc/dc converter, such that it tracks the rotational speed of the motor, that aimed to improve the energy efficiency of the inverter, or the overall energy efficiency of power electronic systems. A detailed energy efficiency model is first developed that takes into account the inverter loss and motor iron loss. Some detailed and in-depth analyses on energy efficiency have been conducted that conclude that the inverter's energy efficiency is largely related to the voltage applied, and the voltage is further closely related to the rotational speed of the motor. Simulations and in-vehicle experiments under a New European Driving Cycle (NEDC) have been conducted that demonstrate the effectiveness of the proposed method on the improvement in energy efficiency of the inverter, as well as the system as a whole.

Calculation of Power Losses in Litz Wire Systems by Coupling FEM and PEEC Method

The frequency-dependent resistance of inductive components with high-frequency litz wires is essential for the design of power electronic systems. A novel simulation approach is demonstrated, which combines the specific benefits of two numerical methods: The magnetic field distribution is calculated by standard finite-element method tools for complex 3-D geometries based on a solid conductor. The resulting magnetic field on cut sections of the conductor is used as boundary condition for the partial element equivalent circuit method. Based on the coupling of these methods, power losses on litz wire level have been calculated taking different bundle structures and pitch lengths into account. The work flow has been automatized and enables simulations of litz wire systems with hundreds of strands. For different simulation setups, the simulations have been verified by comparison to measurements up to 500 kHz. The average deviation is less than 5% in the relevant frequency range.