Feature Papers in Industrial Electronics

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Industrial Electronics".

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 82145

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School of Electrical and Data Engineering, University of Technology Sydney, Sydney, NSW 2007 (PO Box 123), Australia
Interests: renewable energy integration and stabilization; voltage stability; micro grids and smart grids; robust control; electric vehicles; building energy management systems; battery energy storage systems and distributed generations
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Institut de Recherche Dupuy de Lôme (UMR CNRS 6027 IRDL), University of Brest, 29238 Brest, France
Interests: fault detection and diagnosis; failure prognosis; cyberattack detection; fault-resilient control; machine learning
Special Issues, Collections and Topics in MDPI journals

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CISE—Electromechatronic Systems Research Centre, University of Beira Interior, Calçada Fonte do Lameiro, P-6201-001 Covilhã, Portugal
Interests: diagnosis and fault tolerance of electrical machines, power electronics and drives
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

The growing commitment of governments, businesses, and industries towards net zero has provided new opportunities and challenges for energy sectors. The key drivers for energy transition are electrifications, technological innovations, sector couplings, and the introduction of new market structures, e.g., renewable generators, energy storage systems, electric vehicles, and hydrogen fuel cells. There are several challenges regarding the energy transition, for example, energy mix and grid flexibility requirements, the need an electric vehicle (EV) charging infrastructure, a longer-term backup capacity, and managing the impacts of new technologies such as a distributed generation, energy storage systems, and hydrogen fuel cells.

This Special Issue aims to address the emerging and broader issues for a reliable and sustainable operation of power and energy systems and provide a platform to improve interdisciplinary research, sharing the most recent ideas.

The topics of interest for the Special Issue include, but are not limited to, the following:

  1. Demand response and demand-side management in green energy for sustainable power systems;
  2. Modeling and management of EVs;
  3. Green hydrogen technology and integrations with the power network;
  4. Clean energy and recycling;
  5. Cyber-physical systems and wide area monitoring;
  6. Demand flexibility and minimum demand;
  7. Electrifications of fossil fuel-dominated industries;
  8. Power electronics applications in power and energy sectors;
  9. Nonlinear and intelligent control techniques for smart grid;
  10. Energy storage system;
  11. Artificial intelligence and energy;
  12. New energy initiatives.

Prof. Dr. S. M. Muyeen
Prof. Dr. Jahangir Hossain
Prof. Dr. Mohamed Benbouzid
Prof. Dr. Antonio J. Marques Cardoso
Dr. Marco Mussetta
Guest Editors

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Published Papers (23 papers)

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17 pages, 2234 KiB  
Article
Secure Data Transmission of Electronic Health Records Using Blockchain Technology
by Rahul Ganpatrao Sonkamble, Anupkumar M. Bongale, Shraddha Phansalkar, Abhishek Sharma and Shailendra Rajput
Electronics 2023, 12(4), 1015; https://doi.org/10.3390/electronics12041015 - 17 Feb 2023
Cited by 14 | Viewed by 7585
Abstract
Electronic Health Records (EHR) serve as a solid documentation of health transactions and as a vital resource of information for healthcare stakeholders. EHR integrity and security issues, however, continue to be intractable. Blockchain-based EHR architectures, however, address the issues of integrity very effectively. [...] Read more.
Electronic Health Records (EHR) serve as a solid documentation of health transactions and as a vital resource of information for healthcare stakeholders. EHR integrity and security issues, however, continue to be intractable. Blockchain-based EHR architectures, however, address the issues of integrity very effectively. In this work, we suggest a decentralized patient-centered healthcare data management (PCHDM) with a blockchain-based EHR framework to address issues of confidentiality, access control, and privacy of record. This patient-centric architecture keeps the patient at the center of control for secured storage of EHR data. It is effective in the storage environment with the interplanetary file system (IPFS) and blockchain technology. In order to control unauthorized users, the proposed secure password authentication-based key exchange (SPAKE) implements smart contract-based access control to EHR transactions and access policies. The experimental setup comprises four hyperledger fabric nodes with level DB database and IPFS off-chain storage. The framework was evaluated using the public hepatitis dataset, with parameters such as block creation time, transactional computational overhead with encryption key size, and uploading/downloading time with EHR size. The framework enables patient-centric access control of the EHR with the SPAKE encryption algorithm. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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12 pages, 961 KiB  
Article
Numerical Robustness Evaluation of Floating-Point Closed-Loop Control Based on Interval Analysis
by Filippo Savi, Amin Farjudian, Giampaolo Buticchi, Davide Barater and Giovanni Franceschini
Electronics 2023, 12(2), 390; https://doi.org/10.3390/electronics12020390 - 12 Jan 2023
Viewed by 1595
Abstract
Power-electronics-based systems have penetrated into several critical sectors, such as the industry, power generation, energy transmission and distribution, and transportation. In this context, the system’s control, often implemented in real-time processing units, has to meet stringent requirements in terms of safety and repeatability. [...] Read more.
Power-electronics-based systems have penetrated into several critical sectors, such as the industry, power generation, energy transmission and distribution, and transportation. In this context, the system’s control, often implemented in real-time processing units, has to meet stringent requirements in terms of safety and repeatability. Given the growing complexity of the implemented algorithms, floating-point arithmetic is being increasingly adopted for high-performance systems. This paper proposes to assess the numerical stability of the control algorithms by means of an interval analysis. The case study of an electric drive is considered, given the wide adoption of such systems and the importance they hold for the safety of the applications. In particular, two different control strategies—the resonant control and the vector space decomposition—are examined, and a sensitivity analysis based on the proposed technique highlights the different characteristics of the two with respect to numerical stability. The proposed method shows how the resonant control is more robust to variations of the controller gain coefficients with respect to the numerical stability, which could make it the preferred choice for mission-critical electric drive control. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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17 pages, 3317 KiB  
Article
Robust Control of SEDCM by Fuzzy-PSO
by Nagendra Singh, Akhilesh Kumar Sharma, Manish Tiwari, Michał Jasiński, Zbigniew Leonowicz, Stanislav Rusek and Radomir Gono
Electronics 2023, 12(2), 335; https://doi.org/10.3390/electronics12020335 - 9 Jan 2023
Cited by 7 | Viewed by 1799
Abstract
Industries have many rotational operations that are used for design, transport, lift, drilling, rolling, robotics, and many other applications. These rotating applications require a proper controller for accurate control of the operation. Separately excited DC motors (SEDCMs) are versatile and have various industrial [...] Read more.
Industries have many rotational operations that are used for design, transport, lift, drilling, rolling, robotics, and many other applications. These rotating applications require a proper controller for accurate control of the operation. Separately excited DC motors (SEDCMs) are versatile and have various industrial operations because of their specific speed control characteristics. So, for smooth and accurate operation of an SEDC motor, controllers should be used. PI and PID controllers are used in many cases, but they are ineffective for nonlinear load operation. A fuzzy controller is a heuristic controller and can provide automatic control of the operation. Its operation depends on the selection of the correct membership values. This work proposes a novel particle swarm optimization (PSO) technique that would provide the optimum value of the membership for fuzzy controllers for optimum control of the industrial processes. To obtain SEDC results, MATLAB simulation was performed, and the fuzzy controller with novel PSO was implemented. A fuzzy PSO controller used for motor speed control operation obtains a rise time of 0.00026 s, settling time of 0.000214 s, maximum overshoot of zero, and delay time of 0.016 s, which are the best values when compared to PID and PID-Fuzzy controllers. It is observed that the results obtained from the separately excited DC motor using a fuzzy PSO controller improve the dynamic behavior of the motor that so it smoothly tracks the required speed without any more overshoot or oscillation than the PID controller. Such dynamic, stable operation of the motor makes it perfect for industrial as well as household operations. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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16 pages, 4427 KiB  
Article
Cybersecurity Enhancement of Smart Grid: Attacks, Methods, and Prospects
by Usman Inayat, Muhammad Fahad Zia, Sajid Mahmood, Tarek Berghout and Mohamed Benbouzid
Electronics 2022, 11(23), 3854; https://doi.org/10.3390/electronics11233854 - 23 Nov 2022
Cited by 17 | Viewed by 4370
Abstract
Smart grid is an emerging system providing many benefits in digitizing the traditional power distribution systems. However, the added benefits of digitization and the use of the Internet of Things (IoT) technologies in smart grids also poses threats to its reliable continuous operation [...] Read more.
Smart grid is an emerging system providing many benefits in digitizing the traditional power distribution systems. However, the added benefits of digitization and the use of the Internet of Things (IoT) technologies in smart grids also poses threats to its reliable continuous operation due to cyberattacks. Cyber–physical smart grid systems must be secured against increasing security threats and attacks. The most widely studied attacks in smart grids are false data injection attacks (FDIA), denial of service, distributed denial of service (DDoS), and spoofing attacks. These cyberattacks can jeopardize the smooth operation of a smart grid and result in considerable economic losses, equipment damages, and malicious control. This paper focuses on providing an extensive survey on defense mechanisms that can be used to detect these types of cyberattacks and mitigate the associated risks. The future research directions are also provided in the paper for efficient detection and prevention of such cyberattacks. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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19 pages, 4202 KiB  
Article
Wide-Speed-Range Sensorless Control of IPMSM
by Weibin Yang, Hao Guo, Xinxin Sun, Yuanlin Wang, Saleem Riaz and Haider Zaman
Electronics 2022, 11(22), 3747; https://doi.org/10.3390/electronics11223747 - 15 Nov 2022
Cited by 4 | Viewed by 1917
Abstract
A wide-speed-range sensorless control for an IPMSM is deeply studied in this paper, which combines the high-frequency injection (HFI) method and sliding-mode observer (SMO) method. At low-speed range, a rotating high-frequency voltage signal is injected into the IPMSM; the rotor position can be [...] Read more.
A wide-speed-range sensorless control for an IPMSM is deeply studied in this paper, which combines the high-frequency injection (HFI) method and sliding-mode observer (SMO) method. At low-speed range, a rotating high-frequency voltage signal is injected into the IPMSM; the rotor position can be estimated by the HFI method based on the saliency of the IPMSM. At high-speed range, an SMO method based on the extended back electromotive force (EMF) of the IPMSM is utilized to estimate the rotor position. Furthermore, to blend the positions estimated by these two methods, a speed-dependent weight function is designed. The steady-state and dynamic performance of the wide-speed sensorless control are investigated by experiments. In high-speed range, the position estimation errors of the SMO method at different operation points are smaller than 6 el.deg.; in low-speed range, the position estimation errors of the HFI method at different operation points are smaller than 15 el.deg.; and during the transition process, the IPMSM can switch smoothly between the HFI-based and SMO-based sensorless control methods. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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18 pages, 3378 KiB  
Article
Methodology for the Identification of Dust Accumulation Levels in Photovoltaic Panels Based in Heuristic-Statistical Techniques
by Eduardo Perez-Anaya, David A. Elvira-Ortiz, Roque A. Osornio-Rios and Jose A. Antonino-Daviu
Electronics 2022, 11(21), 3503; https://doi.org/10.3390/electronics11213503 - 28 Oct 2022
Cited by 6 | Viewed by 1573
Abstract
The use of renewable energies is increasing around the world in order to deal with the environmental and economic problems related with conventional generation. In this sense, photovoltaic generation is one of the most promising technologies because of the high availability of sunlight, [...] Read more.
The use of renewable energies is increasing around the world in order to deal with the environmental and economic problems related with conventional generation. In this sense, photovoltaic generation is one of the most promising technologies because of the high availability of sunlight, the easiness of maintenance, and the reduction in the costs of installation and production. However, photovoltaic panels are elements that must be located outside in order to receive the sun radiation and transform it into electricity. Therefore, they are exposed to the weather conditions and many environmental factors that can negatively affect the output delivered by the system. One of the most common issues related to the outside location is the dust accumulation in the surface of the panels. The dust particles obstruct the passage of the sunlight, reducing the efficiency of the generation process and making the system prone to experimental long-term faults. Thus, it is necessary to develop techniques that allow us to assess the level of dust accumulation in the panel surface in order to schedule a proper maintenance and avoid losses associated with the reduction of the delivered power and unexpected faults. In this work, we propose a methodology that uses a machine learning approach to estimate different levels of dust accumulation in photovoltaic panels. The developed method takes the voltage, current, temperature, and sun radiance as inputs to perform a statistical feature extraction that describes the behavior of the photovoltaic system under different dust conditions. In order to retain only the relevant information, a genetic algorithm works along with the principal component analysis technique to perform an optimal feature selection. Next, the linear discrimination analysis is carried out using the optimized dataset to reduce the problem dimensionality, and a multi-layer perceptron neural network is implemented as a classifier for discriminating among three different conditions: clean surface, slight dust accumulation, and severe dust accumulation. The proposed methodology is implemented using real signals from a photovoltaic installation, proving to be effective not only to determine if a dust accumulation condition is present but also when maintenance actions must be performed. Moreover, the results demonstrate that the accuracy of the proposed method is always above 94%. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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19 pages, 12527 KiB  
Article
Optimized Torque Performance of a 7-Phase Outer-Rotor Surface-Mounted Permanent Magnet Synchronous Machine for In-Wheel E-Motorcycle Application
by Hamidreza Ghorbani, Mohammadreza Moradian and Mohamed Benbouzid
Electronics 2022, 11(19), 3192; https://doi.org/10.3390/electronics11193192 - 5 Oct 2022
Cited by 1 | Viewed by 1513
Abstract
Four outer rotor surface-mounted permanent magnet synchronous machines (SMPSM), supplied by a seven-phase drive system, are proposed in this study, considering different q (number of stator slot per phase per pole ratio) to achieve a satisfying value of electromagnetic torque and Back-Electromotive Force [...] Read more.
Four outer rotor surface-mounted permanent magnet synchronous machines (SMPSM), supplied by a seven-phase drive system, are proposed in this study, considering different q (number of stator slot per phase per pole ratio) to achieve a satisfying value of electromagnetic torque and Back-Electromotive Force (Back-EMF) with lower torque pulsation. Accordingly, the proposed configurations are investigated, and results are comparatively reported. Thus based on the results, the best-performing configuration, the candidate model, which presents the lowest torque pulsation with a desirable value of Tavg and Back-EMF is selected. In order to demonstrate the advantages of this candidate model, an optimization analysis is performed using 2D Finite Element Analysis (FEA). The resultant values of the variables are applied, designing three optimized models. Performance results of the optimized models demonstrate that TCog reduced noticeably and TRipple declined below 5%. The Artemis Drive-Cycles analysis results are also included for the best-optimized model, considering E-Motorcycle requirements and properties for urban, rural, and motorway driving conditions. Accordingly, in terms of In-Wheel application of the optimized machine, high torque/power density along with high values of PF and efficient performance are provided for E-Motorcycle application. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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20 pages, 4078 KiB  
Article
A New Non-Isolated High-Gain Single-Switch DC–DC Converter Topology with a Continuous Input Current
by Hossein Gholizadeh and Lazhar Ben-Brahim
Electronics 2022, 11(18), 2900; https://doi.org/10.3390/electronics11182900 - 13 Sep 2022
Cited by 14 | Viewed by 2206
Abstract
An ultra-high step-up, non-isolated DC–DC converter with a continuous input current was developed as a result of this research. This converter’s architecture consists of a voltage multiplier cell (VMC), a positive output super lift Luo converter (POSLLC), and a quadratic boost converter (QBS) [...] Read more.
An ultra-high step-up, non-isolated DC–DC converter with a continuous input current was developed as a result of this research. This converter’s architecture consists of a voltage multiplier cell (VMC), a positive output super lift Luo converter (POSLLC), and a quadratic boost converter (QBS) (also referred to as a cascaded boost topology (CBT)). Thus, the bold points of the topologies mentioned earlier enhance the voltage gain of the proposed topology. It is important to note that when the duty cycle is at 50%, the converter attains a voltage gain of ten. Additionally, the constant input current of the topology reduces the current stress on the input filter capacitor. This converter’s topology was investigated and studied under various operating conditions: ideal and non-ideal modes, as well as continuous and discontinuous current modes (CCM/DCM). The converter’s efficiency and voltage gain were also compared to those of newly proposed converters. PLECS and MATLAB software tools were used in the investigation of the proposed topology. A 200 V/200 W prototype was constructed. The experimental results validated the theoretical study and the simulation results. The extracted efficiency was 91%. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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27 pages, 6424 KiB  
Article
Assessment of the Impact of Emitted Radiated Interference Generated by a Selected Rail Traction Unit on the Operating Process of Trackside Video Monitoring Systems
by Jacek Paś, Adam Rosiński, Patryk Wetoszka, Kamil Białek, Tomasz Klimczak and Mirosław Siergiejczyk
Electronics 2022, 11(16), 2554; https://doi.org/10.3390/electronics11162554 - 15 Aug 2022
Cited by 11 | Viewed by 4037
Abstract
The article presents a method for assessing the impact of radiated electromagnetic interference generated by a selected rail traction unit on the operational process of trackside video monitoring systems (VMS). VMSs operated throughout an extensive railway area are responsible for the safety of [...] Read more.
The article presents a method for assessing the impact of radiated electromagnetic interference generated by a selected rail traction unit on the operational process of trackside video monitoring systems (VMS). VMSs operated throughout an extensive railway area are responsible for the safety of people and property transport processes. Emissions of radiated electromagnetic interference generated in an unintended manner by traction vehicles within a railway line lead to interference in the VMS operating process. Based on the knowledge of actual VMS operating process data, spectral characteristics and values of individual components of disturbing signals occurring in the emissions of radiated electromagnetic interference, it is possible to determine the parameters of damage intensities for the devices and elements of this system. Using that data enables determining the VMS reliability parameters within its operating system, for an extensive railway area. The article’s authors first discussed the basic issues associated with VMS, followed by analysing the topic’s current status. They also presented issues related to measuring interference radiated within a rail area, developed a selected operational process model, and determined selected operational indicators for the structures in question. The paper ends with conclusions. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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24 pages, 7590 KiB  
Article
Uncertainty and Sensitivity of the Feature Selective Validation (FSV) Method
by Jacopo Bongiorno and Andrea Mariscotti
Electronics 2022, 11(16), 2532; https://doi.org/10.3390/electronics11162532 - 13 Aug 2022
Cited by 3 | Viewed by 1810
Abstract
The FSV method is a recognized validation tool that initially assesses the similarity between data sets for electromagnetic measurements and models. Its use may be extended to many problems and applications, and in particular, with relation to electrical systems, but it should be [...] Read more.
The FSV method is a recognized validation tool that initially assesses the similarity between data sets for electromagnetic measurements and models. Its use may be extended to many problems and applications, and in particular, with relation to electrical systems, but it should be characterized in terms of its uncertainty, as for measurement tools. To this aim, the Guide to the Expression of Uncertainty in Measurement (GUM) is applied for the propagation of uncertainty from the experimental data to the Feature Selective Validation (FSV) quantities, using Monte Carlo analysis as confirmation, which ultimately remains the most reliable approach to determine the propagation of uncertainty, given the significant FSV non-linearity. Such non-linearity in fact compromises the accuracy of the Taylor approximation supporting the use of first-order derivatives (and derivative terms in general). MCM results are instead more stable and show sensitivity vs. input data uncertainty in the order of 10 to 100, highly depending on the local data samples value. To this aim, normalized sensitivity coefficients are also reported, in an attempt to attenuate the scale effects, redistributing the observed sensitivity values that, however, remain in the said range, up to about 100. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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19 pages, 5051 KiB  
Article
Non-Linear Inductor Models Comparison for Switched-Mode Power Supplies Applications
by Daniele Scirè, Giuseppe Lullo and Gianpaolo Vitale
Electronics 2022, 11(15), 2472; https://doi.org/10.3390/electronics11152472 - 8 Aug 2022
Cited by 15 | Viewed by 4164
Abstract
The use of non-linear power inductors, intended as devices exploited up to a current at which the inductance is halved, is of great interest in switched-mode power supplies (SMPSs). Indeed, it allows the use of lighter and cheaper inductors improving the power density. [...] Read more.
The use of non-linear power inductors, intended as devices exploited up to a current at which the inductance is halved, is of great interest in switched-mode power supplies (SMPSs). Indeed, it allows the use of lighter and cheaper inductors improving the power density. On the other hand, the analysis of SMPSs equipped with non-linear inductors requires appropriate modeling of the inductor reproducing the inductance versus current. This paper compares two main analytical models proposed in the literature: the former is based on a polynomial, and the latter exploits the arctangent function to reproduce the non-linearity of the inductance. Performance is compared by considering the effort of retrieving the model’s parameters, evaluating a current profile by the characteristic equation of the inductor, and exploiting the two models to simulate a switched-mode power supply. Results are given both in terms of computation time and accuracy with reference to experimental values, highlighting the pros and cons of each model. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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8 pages, 1359 KiB  
Article
Algorithm Verification of Single-Shot Relativistic Emittance Proposed Measuring Method
by Leon Feigin, Amir Weinberg and Ariel Nause
Electronics 2022, 11(13), 2092; https://doi.org/10.3390/electronics11132092 - 4 Jul 2022
Cited by 3 | Viewed by 1750
Abstract
A 6 MeV hybrid photo-cathode gun is driving a THz-FEL in Ariel University, as well as other applications. An electron bunch with small transverse emittance is extracted from a copper photo-cathode using a 1 ps UV laser pulse, and then accelerated to a [...] Read more.
A 6 MeV hybrid photo-cathode gun is driving a THz-FEL in Ariel University, as well as other applications. An electron bunch with small transverse emittance is extracted from a copper photo-cathode using a 1 ps UV laser pulse, and then accelerated to a kinetic energy of 6.5 MeV. The Hybrid term is due to the unique standing wave-traveling wave sections in a single RF cavity. Since low emittance is crucial for FEL operation, the characterization of the electron beam requires measuring the transverse emittance, which will be compared with the predicted design and the 3D simulation obtained values, in order to verify their correctness. In this paper, we confirm the use of the multi-slit technique to measure emittance in the Hybrid beam in a single shot and develop a simple and convenient algorithm to be used in the experimental measurements. The experimental analysis requires image processing of the measured data, combined with a custom LabVIEW and Matlab scripts to control the hardware, and analyze the obtained data. Prior to experimentally measuring emittance, we perform a simulated experiment, using a simulated beam from the General Particle Tracer (GPT) code to test these algorithms and scripts, and compare the emittance obtained using the algorithm with GPT’s estimated emittance. Once concluded, this method will allow for a simple, fast and accurate single shot emittance measurement for the Hybrid accelerator beam. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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19 pages, 12624 KiB  
Article
A V2G Enabled Bidirectional Single/Three-Phase EV Charging Interface Using Modular Multilevel Buck PFC Rectifier
by Anekant Jain, Krishna Kumar Gupta, Sanjay K. Jain, Pallavee Bhatnagar and Hani Vahedi
Electronics 2022, 11(12), 1891; https://doi.org/10.3390/electronics11121891 - 16 Jun 2022
Cited by 6 | Viewed by 4528
Abstract
The battery charging power electronics interface of an electric vehicle (EV) must be capable of bidirectional power flow to enable both grid-to-vehicle (G2V) and vehicle-to-grid (V2G) operations. In the presence of a single/three-phase AC supply, the front-end of the EV charger employs a [...] Read more.
The battery charging power electronics interface of an electric vehicle (EV) must be capable of bidirectional power flow to enable both grid-to-vehicle (G2V) and vehicle-to-grid (V2G) operations. In the presence of a single/three-phase AC supply, the front-end of the EV charger employs a power factor correction (PFC) rectifier, which should have the bidirectional capability to facilitate V2G mode. A conventional active rectifier functions in boost mode while performing PFC and voltage regulation. In most of the currently available EVs, however, the battery nominal voltage is low and, hence, a downstream high step-down DC-DC converter and high voltage DC bus capacitor are required in the charging interface. To overcome these issues, this work proposes a bidirectional AC-to-DC buck rectifier topology that can operate in G2V and V2G modes, both in single- and three-phase versions. The proposed topology utilizes the switched capacitors principle to achieve self-balancing of voltages in the capacitors. In addition, it is highly modular in structure. This paper describes the proposed topology, its working and modulation and its applications. The hardware proto model is used to validate the proposed power converter and the control approach to achieve PFC and voltage regulation. In addition, a comparison with other topologies is presented to demonstrate its competence. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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33 pages, 1049 KiB  
Article
Application of the Multiverse Optimization Method to Solve the Optimal Power Flow Problem in Alternating Current Networks
by Andrés Alfonso Rosales Muñoz, Luis Fernando Grisales-Noreña, Jhon Montano, Oscar Danilo Montoya and Alberto-Jesus Perea-Moreno
Electronics 2022, 11(8), 1287; https://doi.org/10.3390/electronics11081287 - 18 Apr 2022
Cited by 6 | Viewed by 2316
Abstract
In this paper, we solve the optimal power flow problem in alternating current networks to reduce power losses. For that purpose, we propose a master–slave methodology that combines the multiverse optimization algorithm (master stage) and the power flow method for alternating current networks [...] Read more.
In this paper, we solve the optimal power flow problem in alternating current networks to reduce power losses. For that purpose, we propose a master–slave methodology that combines the multiverse optimization algorithm (master stage) and the power flow method for alternating current networks based on successive approximation (slave stage). The master stage determines the level of active power to be injected by each distributed generator in the network, and the slave stage evaluates the impact of the proposed solution on each distributed generator in terms of the objective function and the constraints. For the simulations, we used the 10-, 33-, and 69-node radial test systems and the 10-node mesh test system with three levels of distributed generation penetration: 20%, 40%, and 60% of the power provided by the slack generator in a scenario without DGs. In order to validate the robustness and convergence of the proposed optimization algorithm, we compared it with four other optimization methods that have been reported in the specialized literature to solve the problem addressed here: Particle Swarm Optimization, the Continuous Genetic Algorithm, the Black Hole Optimization algorithm, and the Ant Lion Optimization algorithm. The results obtained demonstrate that the proposed master–slave methodology can find the best solution (in terms of power loss reduction, repeatability, and technical conditions) for networks of any size while offering excellent performance in terms of computation time. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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17 pages, 5353 KiB  
Article
Comparative Study of Discrete PI and PR Controller Implemented in SRG for Wind Energy Application: Theory and Experimentation
by Zeineb Touati, Manuel Pereira, Rui Esteves Araújo and Adel Khedher
Electronics 2022, 11(8), 1285; https://doi.org/10.3390/electronics11081285 - 18 Apr 2022
Cited by 10 | Viewed by 2284
Abstract
The Switched Reluctance Generator (SRG) has been widely studied for Wind Energy Conversion Systems (WECS). However, a major drawback of the SRG system adopting the conventional control is the slow response of the DC link voltage controller. In this paper, a Proportional Resonant [...] Read more.
The Switched Reluctance Generator (SRG) has been widely studied for Wind Energy Conversion Systems (WECS). However, a major drawback of the SRG system adopting the conventional control is the slow response of the DC link voltage controller. In this paper, a Proportional Resonant (PR) control strategy is proposed to control the output voltage of the SRG system to improve the fast response. The SRG model has a high non-linearity, which makes the design of controllers a difficult task. For this reason, the important practical engineering aspect of this work is the role played by the SRG model linearization in testing the sensitivity of the PR controller performance to specific parameter changes. The characteristics of steady-state behaviors of the SRG-based WECS under different control approaches are simulated and compared. The controller is implemented on a digital signal processor (TMS320F28379D). The experimental results are carried out using a 250 W 8/6 SRG prototype to assess the performance of the proposed control compared with the traditional Proportional Integral (PI) control strategy. The experimental results show that the PR control enhances the steady-state performance of the SR power generation system in WECS. Compared to PI control, the rise and settling times are reduced by 45% and 43%, respectively, without an overshoot. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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25 pages, 13159 KiB  
Article
A Risk Curtailment Strategy for Solar PV-Battery Integrated Competitive Power System
by Arup Das, Subhojit Dawn, Sadhan Gope and Taha Selim Ustun
Electronics 2022, 11(8), 1251; https://doi.org/10.3390/electronics11081251 - 15 Apr 2022
Cited by 23 | Viewed by 2344
Abstract
Power system networks are becoming more complex and decentralized with the foreword of deregulation in the global power sector. In this scenario, an independent system operator (ISO) is responsible for determining the appropriate actions to deliver stable and quality power to the customers [...] Read more.
Power system networks are becoming more complex and decentralized with the foreword of deregulation in the global power sector. In this scenario, an independent system operator (ISO) is responsible for determining the appropriate actions to deliver stable and quality power to the customers connected to the network at the lowest cost without violating the system security limits. Violations of any security limit may result in system risk. The unstable and non-reliable system always has some drawbacks and is not desirable from the consumer’s point of view. A deregulated power market always keeps the consumer on the advantage side by giving stable, reliable, and less costly power. By using risk assessment tools, we identify the fault conditions and we try to minimize the risk by various uses of sequential programming methods. In this paper, a novel power system risk analysis and congestion management approach are introduced with considering meta-heuristic algorithms i.e., Slime Mould Algorithm (SMA) and Artificial Bee Colony Algorithm (ABC) in renewable energy integrated electricity market. The proposed power system risk analysis is constructed with the help of two risk valuation tools named Conditional-Value-at-risk (CVaR) and Value-at-risk (VaR). The higher negative value of VaR and CVaR represents the higher risk system and lower negative value or towards a positive value of VaR and CVaR denotes the less risk or stable system. The projected method has been experienced on the IEEE 14-bus test system and IEEE 30-bus test system to examine the usefulness of the meta-heuristic algorithm in system risk analysis under the deregulated environment. The importance of renewable energy integration in system risk curtailment has also been depicted in this work: basically, to measure the system’s risk, hence enhancing the system’s reliability and societal welfare. As a result, it will benefit both supply and demand-side participants. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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18 pages, 2086 KiB  
Article
Enhancement of the HILOMOT Algorithm with Modified EM and Modified PSO Algorithms for Nonlinear Systems Identification
by Asif Mahfuz, Mohammad Abdul Mannan and S. M. Muyeen
Electronics 2022, 11(5), 729; https://doi.org/10.3390/electronics11050729 - 26 Feb 2022
Cited by 3 | Viewed by 1943
Abstract
Developing a mathematical model has become an inevitable need in studies of all disciplines. With advancements in technology, there is an emerging need to develop complex mathematical models. System identification is a popular way of constructing mathematical models of highly complex processes when [...] Read more.
Developing a mathematical model has become an inevitable need in studies of all disciplines. With advancements in technology, there is an emerging need to develop complex mathematical models. System identification is a popular way of constructing mathematical models of highly complex processes when an analytical model is not feasible. One of the many model architectures of system identification is to utilize a Local Model Network (LMN). Hierarchical Local Model Tree (HILOMOT) is an iterative LMN training algorithm that uses the axis-oblique split method to divide the input space hierarchically. The split positions of the local models directly influence the accuracy of the entire model. However, finding the best split positions of the local models presents a nonlinear optimization problem. This paper presents an optimized HILOMOT algorithm with enhanced Expectation–Maximization (EM) and Particle Swarm Optimization (PSO) algorithms which includes the normalization parameter and utilizes the reduced-parameter vector. Finally, the performance of the improved HILOMOT algorithm is compared with the existing algorithm by modeling the NOx emission model of a gas turbine and multiple nonlinear test functions of different orders and structures. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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Review

Jump to: Research, Other

20 pages, 1986 KiB  
Review
Control of Permanent Magnet Synchronous Motors for Track Applications
by Paolo Mercorelli
Electronics 2023, 12(15), 3285; https://doi.org/10.3390/electronics12153285 - 31 Jul 2023
Cited by 7 | Viewed by 3624
Abstract
For a wide variety of motion control systems, the PMSM (Permanent Magnet Synchronous Motors) drive is among the best options. The PMSMs, for instance, are frequently used for motors, power tools, and robotics and are currently being explored for high-power uses, including industrial [...] Read more.
For a wide variety of motion control systems, the PMSM (Permanent Magnet Synchronous Motors) drive is among the best options. The PMSMs, for instance, are frequently used for motors, power tools, and robotics and are currently being explored for high-power uses, including industrial motors and vehicle propulsion. Additionally, it has industrial and commercial uses. The PMSM is renowned for its great efficiency, greater power density, exceptional dynamic performance, as well as limited power ripple. The objective of this paper is to review literature that is based on tracking problems through the control of permanent magnet synchronous motors in terms of their control and functionality, including fault detection and performance. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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35 pages, 28762 KiB  
Review
An Overview of Multilevel Inverters Lifetime Assessment for Grid-Connected Solar Photovoltaic Applications
by Shaik Nyamathulla, Dhanamjayulu Chittathuru and S. M. Muyeen
Electronics 2023, 12(8), 1944; https://doi.org/10.3390/electronics12081944 - 20 Apr 2023
Cited by 14 | Viewed by 2875
Abstract
Nowadays, due to advancements in power electronic devices as well as the rise in consumer awareness of the need to protect the environment on a global scale, many people are turning to the use of solar photovoltaic (PV) technology in the distributed power [...] Read more.
Nowadays, due to advancements in power electronic devices as well as the rise in consumer awareness of the need to protect the environment on a global scale, many people are turning to the use of solar photovoltaic (PV) technology in the distributed power generation side. In the field of power electronics, manufacturers need to develop products that have high lifespans. Power electronic device reliability is important for the maintenance of the device and may be scheduled under that information. Rather than preventing failures, reliability can be improved by predicting them. Even though some research has been conducted over the past few years to investigate the reliability of power electronic devices, the reliability is many common circuits has not been investigated and this leads to a big challenge for researchers. In this review paper, an overview of the grid-connected multilevel inverters for PV systems with motivational factors, features, assessment parameters, topologies, modulation schemes of the multilevel inverter, and the selection process for specific applications are presented. In this paper, the findings of a comprehensive reliability analysis of fundamental multilevel inverters are studied. To evaluate the reliability of three basic multilevel inverters, a calculation is made using each component’s mean time before its failure. Two techniques of computation approximate and exact were used to arrive at the final result. To calculate power losses in temperature-sensitive components such as diodes and switches, MATLAB Simulink is employed. In addition, the concept of oversizing photovoltaic (PV) arrays is presented in this study. This concept proposes that energy output may be increased by increasing the size of the PV array under conditions of poor solar irradiation. Finally, the mission-profile-based and Monte Carlo simulation-based methods process flows are discussed for the accurate lifetime prediction and reliability assessments of PV inverters in a real-time scenario, followed by a conclusion with future work. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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23 pages, 4609 KiB  
Review
Multilayer Ceramic Capacitors: An Overview of Failure Mechanisms, Perspectives, and Challenges
by Khaled Laadjal and Antonio J. Marques Cardoso
Electronics 2023, 12(6), 1297; https://doi.org/10.3390/electronics12061297 - 8 Mar 2023
Cited by 12 | Viewed by 13659
Abstract
Along with the growing of population and social and technological improvements, the use of energy and natural resources has risen over the past few decades. The sustainability of using coal, oil, and natural gas as the main energy sources faces, however, substantial obstacles. [...] Read more.
Along with the growing of population and social and technological improvements, the use of energy and natural resources has risen over the past few decades. The sustainability of using coal, oil, and natural gas as the main energy sources faces, however, substantial obstacles. Fuel cells, batteries, and super-capacitors have the highest energy densities, but due to their high-power density and rapid charge-discharge speed, regular dielectric capacitors are becoming more popular for pulsed power applications. High electric breakdown strength and high maximum but low-remnant (zero in the case of linear dielectrics) polarization are necessary for high energy density in dielectric capacitors. The high performance, multi-functionality, and high integration of electronic devices are made possible in large part by the multilayer ceramic capacitors (MLCCs). Due to their low cost, compact size, wide capacitance range, low ESL and ESR, and excellent frequency response, MLCCs play a significant role in contemporary electronic devices. From the standpoint of the underlying theories of energy storage in dielectrics, this paper emphasizes the significant problems and recent advancements in building extremely volumetric-efficient MLCCs. Following a thorough examination of the state-of-the-art, important parameters that may be used to improve energy-storage qualities are highlighted, such as controlling local structure, phase assembly, dielectric layer thickness, microstructure, conductivity, different failure modes, and the specific performance during the failure mechanism. The summary of some conclusions on the impending need for innovative materials and diagnostic methods in high-power/energy density capacitor applications appears at the end of the paper. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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20 pages, 1230 KiB  
Review
Federated Learning for Condition Monitoring of Industrial Processes: A Review on Fault Diagnosis Methods, Challenges, and Prospects
by Tarek Berghout, Mohamed Benbouzid, Toufik Bentrcia, Wei Hong Lim and Yassine Amirat
Electronics 2023, 12(1), 158; https://doi.org/10.3390/electronics12010158 - 29 Dec 2022
Cited by 11 | Viewed by 2830
Abstract
Condition monitoring (CM) of industrial processes is essential for reducing downtime and increasing productivity through accurate Condition-Based Maintenance (CBM) scheduling. Indeed, advanced intelligent learning systems for Fault Diagnosis (FD) make it possible to effectively isolate and identify the origins of faults. Proven smart [...] Read more.
Condition monitoring (CM) of industrial processes is essential for reducing downtime and increasing productivity through accurate Condition-Based Maintenance (CBM) scheduling. Indeed, advanced intelligent learning systems for Fault Diagnosis (FD) make it possible to effectively isolate and identify the origins of faults. Proven smart industrial infrastructure technology enables FD to be a fully decentralized distributed computing task. To this end, such distribution among different regions/institutions, often subject to so-called data islanding, is limited to privacy, security risks, and industry competition due to the limitation of legal regulations or conflicts of interest. Therefore, Federated Learning (FL) is considered an efficient process of separating data from multiple participants to collaboratively train an intelligent and reliable FD model. As no comprehensive study has been introduced on this subject to date, as far as we know, such a review-based study is urgently needed. Within this scope, our work is devoted to reviewing recent advances in FL applications for process diagnostics, while FD methods, challenges, and future prospects are given special attention. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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31 pages, 8106 KiB  
Review
A Systematic Guide for Predicting Remaining Useful Life with Machine Learning
by Tarek Berghout and Mohamed Benbouzid
Electronics 2022, 11(7), 1125; https://doi.org/10.3390/electronics11071125 - 1 Apr 2022
Cited by 37 | Viewed by 7321
Abstract
Prognosis and health management (PHM) are mandatory tasks for real-time monitoring of damage propagation and aging of operating systems during working conditions. More definitely, PHM simplifies conditional maintenance planning by assessing the actual state of health (SoH) through the level of aging indicators. [...] Read more.
Prognosis and health management (PHM) are mandatory tasks for real-time monitoring of damage propagation and aging of operating systems during working conditions. More definitely, PHM simplifies conditional maintenance planning by assessing the actual state of health (SoH) through the level of aging indicators. In fact, an accurate estimate of SoH helps determine remaining useful life (RUL), which is the period between the present and the end of a system’s useful life. Traditional residue-based modeling approaches that rely on the interpretation of appropriate physical laws to simulate operating behaviors fail as the complexity of systems increases. Therefore, machine learning (ML) becomes an unquestionable alternative that employs the behavior of historical data to mimic a large number of SoHs under varying working conditions. In this context, the objective of this paper is twofold. First, to provide an overview of recent developments of RUL prediction while reviewing recent ML tools used for RUL prediction in different critical systems. Second, and more importantly, to ensure that the RUL prediction process from data acquisition to model building and evaluation is straightforward. This paper also provides step-by-step guidelines to help determine the appropriate solution for any specific type of driven data. This guide is followed by a classification of different types of ML tools to cover all the discussed cases. Ultimately, this review-based study uses these guidelines to determine learning model limitations, reconstruction challenges, and future prospects. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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Other

Jump to: Research, Review

7 pages, 822 KiB  
Perspective
Quo Vadis Machine Learning-Based Systems Condition Prognosis?—A Perspective
by Mohamed Benbouzid and Tarek Berghout
Electronics 2023, 12(3), 527; https://doi.org/10.3390/electronics12030527 - 19 Jan 2023
Cited by 3 | Viewed by 1121
Abstract
Data-driven prognostics and health management (PHM) is key to increasing the productivity of industrial processes through accurate maintenance planning. The increasing complexity of the systems themselves, in addition to cyber-physical connectivity, has brought too many challenges for the discipline. As a result, data [...] Read more.
Data-driven prognostics and health management (PHM) is key to increasing the productivity of industrial processes through accurate maintenance planning. The increasing complexity of the systems themselves, in addition to cyber-physical connectivity, has brought too many challenges for the discipline. As a result, data complexity challenges have been pushed back to include more decentralized learning challenges. In this context, this perspective paper describes these challenges and provides future directions based on a relevant state-of-the-art review. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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