Digital Twins and Robust Design Optimization for Greener Manufacturing of Electrical Machines and Devices

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

Deadline for manuscript submissions: 15 September 2024 | Viewed by 10700

Special Issue Editors


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Guest Editor
Department of Power Electronics and Drives, Széchenyi István University, 9026 Győr, Hungary
Interests: optimization; robust design optimization; modeling; numerical analysis; electrical machines; transformers; applied and computational mathematics
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Theory of Electrical Engineering, University of West Bohemia, 30614 Pilsen, Czech Republic
Interests: optimization; robust design optimization; modeling; numerical analysis; electrical machines; applied and computational mathematics
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Automation, Széchenyi István University, H-9026 Győr, Hungary
Interests: control system synthesis; computer-aided instruction; electrical machines; finite element analysis; magnetic hysteresis; nonlinear control systems; state–space methods
Special Issues, Collections and Topics in MDPI journals

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Guest Editor

Special Issue Information

Dear Colleagues,

The implementation and application of green manufacturing processes, which can reduce waste production and enhance the utilization of raw materials, are essential to the manufacturing of electrical machines and devices.

In order to achieve these goals, novel numerical modelling and optimization approaches need to be developed, where the goal is to minimize the losses of an electrical machine and reduce the price of the product. A good, green design should be insensitive to parameter changes or manufacturing tolerances.

Due to the rapid growth of Digital Twin technology, as one of the pillars of Industry 4.0, many advanced technologies, such as cloud computing, artificial intelligence; Big Data analytics; and data science, can be integrated. Digital Twin technology ensures not only that numerical models of the produced electrical devices are fine-tuned, but that highly sophisticated numerical models can be used for the real-time control of manufacturing processes, monitoring or predictive maintenance of manufactured machines.

The Special Issue is open for contributions that show how modern numerical technologies are integrated and deployed as Digital Twins and how robust design optimization techniques can support the greener manufacturing of electric machines and electrical devices.

Topics of interest for this Special Issue include, but are not limited to:

  • Digital Twins, predictive maintenance, Industry 4.0;
  • System-level modelling, multi-domain automatic analysis tools, co-simulations, etc.;
  • New numerical and analytical modelling techniques;
  • Advanced modelling (electromagnetic, thermal, NVH, mechanical, EMC, insulation, etc.);
  • Advanced models for diagnosis;
  • Electromagnetic materials, iron losses, and additional losses;
  • Optimization techniques;
  • Advanced testing (multiphysics performances, standard tests, accelerated life testing, etc.);
  • Optimization and learning under uncertainty;
  • Model-based software development and validation of optimization of electrical machines or electric devices;
  • Surrogate and reduced-order modelling of electric machines and electric devices.

Dr. Tamás Orosz
Dr. David Pánek
Prof. Dr. Miklos Kuczmann
Prof. Dr. Anton Rassõlkin
Guest Editors

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Keywords

  • robust design optimization
  • digital twins
  • electrical machines

Published Papers (8 papers)

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Research

20 pages, 6023 KiB  
Article
A Method for Assessing the Degradation of PVC-Insulated Low-Voltage Distribution Cables Exposed to Short-Term Cyclic Aging
by Semih Bal and Zoltán Ádám Tamus
Electronics 2024, 13(6), 1085; https://doi.org/10.3390/electronics13061085 - 15 Mar 2024
Viewed by 680
Abstract
The distribution grid comprises cables with diverse constructions. The insulating material used in low-voltage (LV) distribution cables is predominantly PVC. Furthermore, the presence of cables with different structures in the grid poses challenges in detecting the aging of the cable network. Finding a [...] Read more.
The distribution grid comprises cables with diverse constructions. The insulating material used in low-voltage (LV) distribution cables is predominantly PVC. Furthermore, the presence of cables with different structures in the grid poses challenges in detecting the aging of the cable network. Finding a universal and dependable condition-monitoring technique that can be applied to various types of cables is indeed a challenge. The diverse construction and materials used in different cables make it difficult to identify a single monitoring approach that can effectively assess the condition of all cables. To address this issue, this study aims to compare the thermal aging behavior of different LV distribution cables with various structures, i.e., one cable contains a PVC belting layer, while the other contains filler material. The growing adoption of distributed generation sources, electric vehicles, and new consumer appliances in low-voltage distribution grids can lead to short, repetitive overloads on the low-voltage cable network. Hence, these cable samples were exposed to short-term cyclic accelerated aging in the climate chamber at 110 °C. The cable’s overall behavior under thermal stress was evaluated through frequency and time domain electrical measurements (including tan δ and extended voltage response) and a mechanical measurement (Shore D). The tan δ was measured in the frequency range of 20 Hz–500 kHz by using the Wayne-Kerr impedance analyzer. The extended voltage response measurement was conducted using a C# application developed in-house specifically for laboratory measurements in the .NET environment. The study observed a strong correlation between the different measurement methods used, indicating that electrical methods have the potential to be adopted as a non-destructive condition-monitoring technique. Full article
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17 pages, 3098 KiB  
Article
High-Frequency Modelling of Electrical Machines for EMC Analysis
by Yerai Moreno, Aritz Egea, Gaizka Almandoz, Gaizka Ugalde, Ander Urdangarin and Roberto Moreno
Electronics 2024, 13(4), 787; https://doi.org/10.3390/electronics13040787 - 17 Feb 2024
Viewed by 1146
Abstract
The trend towards electrification in mobility has led to the increased use of silicon carbide (SiC) semiconductors. These semiconductors are more efficient but also present challenges related to electromagnetic interference (EMI) due to their higher voltage derivatives. This paper introduces a new high-frequency [...] Read more.
The trend towards electrification in mobility has led to the increased use of silicon carbide (SiC) semiconductors. These semiconductors are more efficient but also present challenges related to electromagnetic interference (EMI) due to their higher voltage derivatives. This paper introduces a new high-frequency impedance model for electrical machines. The proposed model distinguishes itself from existing approaches by being entirely derived from Finite Element Method (FEM) simulations, which include capacitances in the magnetic simulation. This approach achieves a balance between computational efficiency and high accuracy across the entire frequency spectrum, ranging from 100 Hz to 50 MHz. The model provides valuable insights during the design phase and was rigorously validated using data from 28 samples of an industrial machine. Full article
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15 pages, 4629 KiB  
Article
Classification of Partial Discharge in Vehicle-Mounted Cable Termination of High-Speed Electric Multiple Unit: A Machine Learning-Based Approach
by Yanhua Yang, Jiali Li, Zhenbao Chen, Yong-Chao Liu, Kui Chen, Kai Liu, Dong-Li Xin, Guoqiang Gao and Guangning Wu
Electronics 2024, 13(3), 495; https://doi.org/10.3390/electronics13030495 - 24 Jan 2024
Cited by 1 | Viewed by 913
Abstract
This paper presents a machine learning-based approach to identify and separate partial discharge (PD) and two typical pulse interference (PI) signals in the vehicle-mounted cable terminations of high-speed electric multiple units (EMUs). First, a test platform was established to capture PD and two [...] Read more.
This paper presents a machine learning-based approach to identify and separate partial discharge (PD) and two typical pulse interference (PI) signals in the vehicle-mounted cable terminations of high-speed electric multiple units (EMUs). First, a test platform was established to capture PD and two typical PI signals in these terminations. The acquired signals were then processed using the square envelope method to extract feature parameters, such as the rise time proportion, the left–right symmetry, and the upper–lower symmetry. PD signal classification was carried out on these signals, utilizing waveform parameters derived from a hierarchical clustering algorithm. The results validate that the extracted feature components effectively classify and separate PD and two typical PI signals in the vehicle-mounted cable terminations of high-speed EMUs. Full article
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20 pages, 16145 KiB  
Article
A Digital Twinning Approach for the Internet of Unmanned Electric Vehicles (IoUEVs) in the Metaverse
by Mohsen Ebadpour, Mohammad (Behdad) Jamshidi, Jakub Talla, Hamed Hashemi-Dezaki and Zdeněk Peroutka
Electronics 2023, 12(9), 2016; https://doi.org/10.3390/electronics12092016 - 26 Apr 2023
Cited by 4 | Viewed by 1503
Abstract
Regarding the importance of the Internet of Things (IoT) and the Metaverse as two practical emerging technologies to enhance the digitalization of public transportation systems, this article introduces an approach for the improvement of IoT and unmanned electric vehicles in the Metaverse, called [...] Read more.
Regarding the importance of the Internet of Things (IoT) and the Metaverse as two practical emerging technologies to enhance the digitalization of public transportation systems, this article introduces an approach for the improvement of IoT and unmanned electric vehicles in the Metaverse, called the Internet of Unmanned Electric Vehicles (IoUEVs). This research includes two important contributions. The first contribution is the description of a framework for how unmanned electric vehicles can be used in the Metaverse, and the second contribution is the creation of a digital twin for an unmanned electric vehicle. In the digital twin section, which is the focus of this research, we present a digital twin of an electronic differential system (EDS) in which the stability has been improved. Robust fuzzy logic algorithm-based speed controllers are employed in the EDS to independently control the EV wheels driven by high-performance brushless DC (BLDC) electric motors. In this study, the rotor position information of the motors, which is estimated from the low-precision Hall-effect sensors mounted on the motors’ shafts, is combined and converted to a set of common switching signals for empowering the EDS of the electric vehicle traction drive system. The proposed digital twin EDS relies on an accurate Hall sensor signals-based synchronizing/locking strategy with a dynamic steering pattern capable of running in severe road conditions with different surface profiles to ensure the EV’s stability. Unlike recent EDSs, the proposed digital twinning approach includes a simple practical topology with no need for auxiliary infrastructures, which is able to reduce mechanical losses and stresses and can be adapted to IoUEVs more effectively. Full article
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22 pages, 7037 KiB  
Article
Hydraulic Integrated Interconnected Regenerative Suspension: Sensitivity Analysis and Parameter Optimization
by Sijing Guo, Liang Chen, Yu Pan, Xuxiang Wang and Gangfeng Tan
Electronics 2023, 12(4), 891; https://doi.org/10.3390/electronics12040891 - 9 Feb 2023
Cited by 2 | Viewed by 1287
Abstract
Hydraulic integrated interconnected regenerative suspension (HIIRS) is a novel suspension system that can simultaneously harvest the vibration energy in the suspension and enhance the vehicle dynamics. The parameter sensitivity of the HIIRS system is analyzed and the significant parameters are optimized in this [...] Read more.
Hydraulic integrated interconnected regenerative suspension (HIIRS) is a novel suspension system that can simultaneously harvest the vibration energy in the suspension and enhance the vehicle dynamics. The parameter sensitivity of the HIIRS system is analyzed and the significant parameters are optimized in this paper. Specifically, a half-vehicle model with the HIIRS is established. Based on the model, the parameter sensitivity of the hydraulic system is analyzed with three objectives, ride comfort, road holding, and average energy harvesting power. The parameters considered in this study are more abundant than those in previous related studies, including hydraulic cylinder inner diameter, hydraulic motor displacement, resistance, initial system pressure, and accumulator parameters. It turns out that the most sensitive parameters are the inner diameter of the hydraulic cylinder, the resistance, and the displacement of the hydraulic motor. To further study the performances that the HIIRS could present, both the single-objective optimization and the multi-objective optimization problems are solved and compared with the optimized traditional suspensions. The optimized HIIRS performs better in ride comfort and road holding than the optimized traditional suspension and anti-roll bar suspension. Different from the previous suspension optimization design, multi-objective optimization not only considers the traditional performance of the suspension but also incorporates the energy harvesting characteristics into the optimization objective. In the multi-objective optimization, a Pareto front is obtained, which shows that the ride comfort conflicts with the road holding and the energy harvesting power, while road holding and energy harvesting power did not conflict. The Pareto front shows that the optimized HIIRS is superior to the traditional suspension in ride comfort and road holding, and also harvests considerable energy. Full article
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15 pages, 1889 KiB  
Article
Linear-Matrix-Inequality-Based Controller and Observer Design for Induction Machine
by Zoltán Németh and Miklós Kuczmann
Electronics 2022, 11(23), 3894; https://doi.org/10.3390/electronics11233894 - 24 Nov 2022
Cited by 2 | Viewed by 1157
Abstract
The modeling and drive control of electric machines are still actively researched scientific topics. Most of the existing models contain parameters that have no physical content or cannot be measured at all. For this reason, the use of observers in modern drive control [...] Read more.
The modeling and drive control of electric machines are still actively researched scientific topics. Most of the existing models contain parameters that have no physical content or cannot be measured at all. For this reason, the use of observers in modern drive control algorithms is necessary. The main goal of this paper is to present the mathematical formalism of a linear matrix inequality (LMI)-based controller-observer design for a tensor product (TP) transformation-based model, including its implementation in a simulation environment. Based solely upon simulation results, the designed observer can provide a stable and accurate state space variable, regardless of the highly nonlinear induction machine model. Full article
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23 pages, 6396 KiB  
Article
Optimal Solution for Frequency and Voltage Control of an Islanded Microgrid Using Square Root Gray Wolf Optimization
by Aftab Ahmed Almani, XueShan Han, Farhana Umer, Rizwan ul Hassan, Aamir Nawaz, Aamer Abbas Shah and Ehtasham Mustafa
Electronics 2022, 11(22), 3644; https://doi.org/10.3390/electronics11223644 - 8 Nov 2022
Cited by 3 | Viewed by 1157
Abstract
Voltage and frequency deviation in the islanded operation of a microgrid (MG), due to the uncertainty and lack of inertia in the selection of optimal proportional integral (PI) controller gain, is a challenging task. Although various optimization algorithms have been proposed to achieve [...] Read more.
Voltage and frequency deviation in the islanded operation of a microgrid (MG), due to the uncertainty and lack of inertia in the selection of optimal proportional integral (PI) controller gain, is a challenging task. Although various optimization algorithms have been proposed to achieve this task, most of them require a large number of iterations and are time intensive, making them inefficient for real-time applications. Gray wolf optimization (GWO), a new meta-heuristic algorithm, addresses these issues and has many advantages, including simplicity due to fewer control parameters, flexibility, and globalism. This paper proposes a simple and efficient modified algorithm, called square root gray wolf optimization (SRGWO) algorithm, to realize superior hunting performance. SRGWO is verified using twenty-three benchmark test functions. The algorithm is applied for optimal voltage and frequency regulation of a photovoltaic-based microgrid system operating in the islanded mode during distributed generation insertion and load change conditions. The voltage and frequency gain parameters of the PI controller are optimized. A comparison of the simulation results of the SRGWO algorithm with those of the original gray wolf algorithm (GWO), particle swarm optimization (PSO), augmented gray wolf optimization (AGWO), enhanced gray wolf optimization (EGWO), and gravitational search algorithm (GSA) reveal that the proposed SRGWO algorithm significantly improves system performance while maintaining its simplicity and easy implementation. Furthermore, the SRGWO algorithm obtains the minimum fitness function value in fewer iterations than other algorithms. Moreover, it improves the power quality of the system with regard to minimum total harmonic distortion. Full article
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23 pages, 2294 KiB  
Article
Flexibility Optimization in Robust Co-Optimization of Combined Power System and Gas Networks Using Transmission Lines’ Switching
by Mohammad Ghasemloo, Maryam A. Hejazi and Hamed Hashemi-Dezaki
Electronics 2022, 11(17), 2647; https://doi.org/10.3390/electronics11172647 - 24 Aug 2022
Cited by 1 | Viewed by 1272
Abstract
The operational flexibility in electricity networks with a high penetration rate of renewable resources has received a great deal of attention. In several research works, gas network constraints have been studied in operational flexibility studies because specific characteristics of the gas-fired units play [...] Read more.
The operational flexibility in electricity networks with a high penetration rate of renewable resources has received a great deal of attention. In several research works, gas network constraints have been studied in operational flexibility studies because specific characteristics of the gas-fired units play a major role in procuring flexibility. However, the literature shows that the interval range of the uncertainty set has been assumed to be deterministic in most of the available research works. This paper tries to fill the research gap about stochastic modeling of the interval range of the uncertainty set. It considers the uncertainty set’s interval range an uncertain parameter, allowing optimal scheduling with less conservative assumptions. In addition, transmission lines’ switching is considered to optimize the network topology when the N-1 reliability measure is adopted. As a nonconvex problem, the recourse decision level would be a mixed-integer program (MIP), for which an exact nested column-and-constraint generation algorithm is used to find the best solutions. The proposed method was applied to IEEE six-bus and 39-bus test systems, interconnecting their corresponding gas networks. The test results infer that in a specified risk level for the IEEE six-bus and 39-bus test systems, with a rather slight increase (7.3% and 065%) in the operation cost, a large reduction (89% and 99%) in the out-of-sample cost could be obtained, respectively. The test results illustrate the advantages of the proposed method, using the variable interval range of the uncertainty set and corrective transmission lines’ switching. In addition, it was shown that if transmission switching is not considered, the total cost rises up to 18.8%. Full article
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