Energies

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30 pages, 22281 KiB

Open AccessArticle

Optimization of Stator Structure for Improved Accuracy in Variable Reluctance Resolvers Using Advanced Machine Learning Techniques

by Wentao Li, Qiankun Liu, Siyang Ye and Surong Huang

Energies 2024, 17(21), 5454; https://doi.org/10.3390/en17215454 - 31 Oct 2024

Viewed by 436

Abstract

This study presents an optimized design for a Segmented Sinusoidal Parameter Winding with Magnetic Wedge Variable Reluctance Resolver (SSPWMW-VRR), addressing challenges like winding asymmetry and harmonic distortion in conventional designs. By integrating particle swarm optimization (PSO) for winding design, magnetic equivalent circuit (MEC) [...] Read more.

This study presents an optimized design for a Segmented Sinusoidal Parameter Winding with Magnetic Wedge Variable Reluctance Resolver (SSPWMW-VRR), addressing challenges like winding asymmetry and harmonic distortion in conventional designs. By integrating particle swarm optimization (PSO) for winding design, magnetic equivalent circuit (MEC) analysis for leakage flux, and machine learning techniques (XGBoost and Multi-Layer Perceptron), the stator slot shape was fine-tuned for improved accuracy. XGBoost outperformed MLP in prediction accuracy with a mean absolute error (MAE) of 0.1172. Finite element analysis (FEA) simulations and experimental validation demonstrated a reduction in position errors from ±30′ in conventional VRRs to ±5′ in the optimized design, along with significant harmonic reduction. Full article

(This article belongs to the Special Issue Applications of Electromagnetism in Energy Efficiency)

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21 pages, 3432 KiB

Open AccessArticle

Mathematical Model of a Nonlinear Electromagnetic Circuit Based on the Modified Hamilton–Ostrogradsky Principle

by Andriy Chaban, Andrzej Popenda, Tomasz Perzyński, Andrzej Szafraniec and Vitaliy Levoniuk

Energies 2024, 17(21), 5365; https://doi.org/10.3390/en17215365 - 28 Oct 2024

Viewed by 472

Abstract

This paper presents a mathematical model of a typical lumped-parameter electromagnetic assembly, which consists of two subassemblies: one includes a magnetic circuit and the other with selected elements of electric circuits. An interdisciplinary research approach is used, which assumes the use of a [...] Read more.

This paper presents a mathematical model of a typical lumped-parameter electromagnetic assembly, which consists of two subassemblies: one includes a magnetic circuit and the other with selected elements of electric circuits. An interdisciplinary research approach is used, which assumes the use of a modified integral method based on the variational Hamilton–Ostrogradsky principle. The modification of the method is the extension of the Lagrange function by two components. The first one reflects the dissipation of electromagnetic energy in the system, while the second one reflects the effect of external non-potential forces acting on the electromagnetic system. This approach allows for the avoidance of the inconvenience of the classical theory, which assumes the decomposition of the entire integrated system into individual electrical subsystems. The state equations of the electromagnetic subassembly are presented solely on the basis of the energy approach, which in turn allows taking into account various latent motions in the system, because the equations are derived based on non-stationary constraints between subsystems. The adopted theory allows for the formulation of the model of the system in a vector form, which gives much more possibilities for the analysis of higher-order electromagnetic circuits. Another important advantage is that the state equations of the considered electrical object are given in Cauchy normal form. In this way, the equations can be integrated both explicitly and implicitly. The results of computer simulations are presented in graphical form, analysed, and discussed. Full article

(This article belongs to the Special Issue Applications of Electromagnetism in Energy Efficiency)

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28 pages, 41617 KiB

Open AccessArticle

Application of the FDTD Method to Analyze the Influence of Brick Complexity on Electromagnetic Wave Propagation

by Agnieszka Choroszucho, Tomasz Szczegielniak and Dariusz Kusiak

Energies 2024, 17(20), 5168; https://doi.org/10.3390/en17205168 - 17 Oct 2024

Viewed by 464

Abstract

This article presents a numerical analysis of the effects related to the propagation of electromagnetic waves in an area containing a non-ideal, non-uniform, and absorbing dielectric. The analysis concerns the influence of electrical parameters, the structure of the building material, and the layering [...] Read more.

This article presents a numerical analysis of the effects related to the propagation of electromagnetic waves in an area containing a non-ideal, non-uniform, and absorbing dielectric. The analysis concerns the influence of electrical parameters, the structure of the building material, and the layering of the wall on the values of the electric field intensity. A multivariate analysis was carried out with different conductivity values. Homogeneous materials (e.g., solid brick) can be analyzed using the analytical method. In the case of complex materials containing, e.g., hollows (brick with hollows, hollow block), it is necessary to use the numerical method. The FDTD (finite difference time domain) method was used to assess the dependence of the electric field intensity on the layering, the length of hollows in bricks, and the material loss. In order to check the correctness of the adopted numerical assumptions, a series of tests related to the discretization of the model was carried out. The article also presents the influence of changing the length of hollows in bricks on the values of the electric field intensity at a frequency of 2.4 GHz. The instantaneous field distributions and maximum values of the electric field intensity are presented. In the model with a two-layer wall, regardless of the conductivity, the field values were the same for the two models, where the difference in the percentage of ceramic mass in the brick was 8%. A 12% decrease in the percentage of ceramic mass in the brick resulted in a 15% increase in the value of the area between a single-layer and a double-layer wall made of clinker bricks. At a conductivity of 0.04 S/m for a single-layer wall, the field values were similar for all brick variants. Full article

(This article belongs to the Special Issue Applications of Electromagnetism in Energy Efficiency)

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15 pages, 4630 KiB

Open AccessArticle

Enhanced Indoor Positioning System Using Ultra-Wideband Technology and Machine Learning Algorithms for Energy-Efficient Warehouse Management

by Dominik Gnaś, Dariusz Majerek, Michał Styła, Przemysław Adamkiewicz, Stanisław Skowron, Monika Sak-Skowron, Olena Ivashko, Józef Stokłosa and Robert Pietrzyk

Energies 2024, 17(16), 4125; https://doi.org/10.3390/en17164125 - 19 Aug 2024

Viewed by 895

Abstract

The following article presents a proprietary real-time localization system using temporal analysis techniques and detection and localization algorithms supported by machine learning mechanisms. It covers both the technological aspects, such as proprietary electronics, and the overall architecture of the system for managing human [...] Read more.

The following article presents a proprietary real-time localization system using temporal analysis techniques and detection and localization algorithms supported by machine learning mechanisms. It covers both the technological aspects, such as proprietary electronics, and the overall architecture of the system for managing human and fixed assets. Its origins lie in the ever-increasing degree of automation in the management of company processes and the energy optimization associated with reducing the execution time of tasks in an intelligent building supported by in-building navigation. The positioning and tracking of objects in the presented system was realized using ultra-wideband radio tag technology. An exceptional focus has been placed on reducing the energy requirements of the components in order to maximize battery runtime, generate savings in terms of more efficient management of other energy consumers in the building and increase the equipment’s overall lifespan. Full article

(This article belongs to the Special Issue Applications of Electromagnetism in Energy Efficiency)

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16 pages, 5440 KiB

Open AccessArticle

Detection and Determination of User Position Using Radio Tomography with Optimal Energy Consumption of Measuring Devices in Smart Buildings

by Michał Styła, Edward Kozłowski, Paweł Tchórzewski, Dominik Gnaś, Przemysław Adamkiewicz, Jan Laskowski, Sylwia Skrzypek-Ahmed, Arkadiusz Małek and Dariusz Kasperek

Energies 2024, 17(11), 2757; https://doi.org/10.3390/en17112757 - 5 Jun 2024

Viewed by 707

Abstract

The main objective of the research presented in the following work was the adaptation of reflection-radar technology in a detection and navigation system using radio-tomographic imaging techniques. As key aspects of this work, the energy optimization of high-frequency transmitters can be considered for [...] Read more.

The main objective of the research presented in the following work was the adaptation of reflection-radar technology in a detection and navigation system using radio-tomographic imaging techniques. As key aspects of this work, the energy optimization of high-frequency transmitters can be considered for use inside buildings while maintaining user safety. The resulting building monitoring and control system using a network of intelligent sensors supported by artificial intelligence algorithms, such as logistic regression or neural networks, should be considered an outcome. This paper discusses the methodology for extracting information from signal echoes and how they were transported and aggregated. The data extracted in this way were used to support user navigation through a building, optimize energy based on presence information, and increase the facility’s overall security level. A band from 5 GHz to 6 GHz was chosen as the carrier frequency of the signals, representing a compromise between energy expenditure, range, and the properties of wave behavior in contact with different types of matter. The system includes proprietary hardware solutions that allow parameters to be adjusted over the entire range and guarantee adaptation for RTI (radio tomography imaging) technology. Full article

(This article belongs to the Special Issue Applications of Electromagnetism in Energy Efficiency)

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17 pages, 11293 KiB

Open AccessArticle

Optimal Rotor Design and Analysis of Energy-Efficient Brushless DC Motor-Driven Centrifugal Monoset Pump for Agriculture Applications

by Richard Pravin Antony, Pongiannan Rakkiya Goundar Komarasamy, Narayanamoorthi Rajamanickam, Roobaea Alroobaea and Yasser Aboelmagd

Energies 2024, 17(10), 2280; https://doi.org/10.3390/en17102280 - 9 May 2024

Cited by 1 | Viewed by 1394

Abstract

The agricultural sector emphasizes sustainable development and energy efficiency, particularly in optimizing water pumping systems for irrigation. Brushless DC (BLDC) motors are the preferred prime mover over induction motors due to their high efficiency in such applications. This article details the rotor design [...] Read more.

The agricultural sector emphasizes sustainable development and energy efficiency, particularly in optimizing water pumping systems for irrigation. Brushless DC (BLDC) motors are the preferred prime mover over induction motors due to their high efficiency in such applications. This article details the rotor design and analysis of an energy-efficient BLDC motor with specifications of 1 hp, 3000 rpm, and 48 V, specifically tailored for a centrifugal monoset pump for irrigation. The focus lies in achieving optimal energy efficiency through grey wolf optimization (GWO) algorithm in the rotor design to determine optimal dimensions of the Neodymium Iron Boron (NdFeB) magnet as well as its grade. The finite element method analysis software, MagNet, is used to model and analyze the BLDC motor. The motor parameters, such as speed, torque, flux functions, temperature, and efficiency, are analyzed. For performance comparison, the same model with different magnet models is also analyzed. Validation via 3D finite element analysis highlights improvements in magnet flux linkage, stator tooth flux density, and rotor inertia with increased magnet thickness. Simulation results affirm the consistent performance of the designed BLDC motor, preferably when efficiency is increased. This efficiency and the constant speed lead to an improvement in the overall conversion efficiency of 7% within its operating range, affirming that the motor pump system is energy-efficient. Full article

(This article belongs to the Special Issue Applications of Electromagnetism in Energy Efficiency)

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17 pages, 41503 KiB

Open AccessArticle

Optimizing the Neural Network Loss Function in Electrical Tomography to Increase Energy Efficiency in Industrial Reactors

by Monika Kulisz, Grzegorz Kłosowski, Tomasz Rymarczyk, Jolanta Słoniec, Konrad Gauda and Wiktor Cwynar

Energies 2024, 17(3), 681; https://doi.org/10.3390/en17030681 - 31 Jan 2024

Cited by 2 | Viewed by 913

Abstract

This paper presents innovative machine-learning solutions to enhance energy efficiency in electrical tomography for industrial reactors. Addressing the key challenge of optimizing the neural model’s loss function, a classifier tailored to precisely recommend optimal loss functions based on the measurement data is designed. [...] Read more.

This paper presents innovative machine-learning solutions to enhance energy efficiency in electrical tomography for industrial reactors. Addressing the key challenge of optimizing the neural model’s loss function, a classifier tailored to precisely recommend optimal loss functions based on the measurement data is designed. This classifier recommends which model, equipped with given loss functions, should be used to ensure the best reconstruction quality. The novelty of this study lies in the optimal adjustment of the loss function to a specific measurement vector, which allows for better reconstructions than that by traditional models trained based on a constant loss function. This study presents a methodology enabling the development of an optimal loss function classifier to determine the optimal model and loss function for specific datasets. The approach eliminates the randomness inherent in traditional methods, leading to more accurate and reliable reconstructions. In order to achieve the set goal, four models based on a simple LSTM network structure were first trained, each connected with various loss functions: HMSE (half mean squared error), Huber, l1loss (L1 loss for regression tasks—mean absolute error), and l2loss (L2 loss for regression tasks—mean squared error). The best classifier training results were obtained for support vector machines. The quality of the obtained reconstructions was evaluated using three image quality indicators: PSNR, ICC, and MSE. When applied to simulated cases and real measurements from the Netrix S.A. laboratory, the classifier demonstrated effective performance, consistently recommending models that produced reconstructions that closely resembled the real objects. Such a classifier can significantly optimize the use of EIT in industrial reactors by increasing the accuracy and efficiency of imaging, resulting in improved energy management and efficiency. Full article

(This article belongs to the Special Issue Applications of Electromagnetism in Energy Efficiency)

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17 pages, 5842 KiB

Open AccessArticle

Algorithms for Optimizing Energy Consumption for Fermentation Processes in Biogas Production

by Grzegorz Rybak, Edward Kozłowski, Krzysztof Król, Tomasz Rymarczyk, Agnieszka Sulimierska, Artur Dmowski and Piotr Bednarczuk

Energies 2023, 16(24), 7972; https://doi.org/10.3390/en16247972 - 8 Dec 2023

Cited by 1 | Viewed by 915

Abstract

Problems related to reducing energy consumption constitute an important basis for scientific research worldwide. A proposal to use various renewable energy sources, including creating a biogas plant, is emphasized in the introduction of this article. However, the indicated solutions require continuous monitoring and [...] Read more.

Problems related to reducing energy consumption constitute an important basis for scientific research worldwide. A proposal to use various renewable energy sources, including creating a biogas plant, is emphasized in the introduction of this article. However, the indicated solutions require continuous monitoring and control to maximise the installations’ effectiveness. The authors took up the challenge of developing a computer solution to reduce the costs of maintaining technological process monitoring systems. Concept diagrams of a metrological system using multi-sensor techniques containing humidity, temperature and pressure sensors coupled with Electrical Impedance Tomography (EIT) sensors were presented. This approach allows for effective monitoring of the anaerobic fermentation process. The possibility of reducing the energy consumed during installation operation was proposed, which resulted in the development of algorithms for determining alarm states, which are the basis for controlling the frequency of technological process measurements. Implementing the idea required the preparation of measurement infrastructure and an analytical engine based on AI techniques, including an expert system and developed algorithms. Numerous time-consuming studies and experiments have confirmed reduced energy consumption, which can be successfully used in biogas production. Full article

(This article belongs to the Special Issue Applications of Electromagnetism in Energy Efficiency)

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