Search Results (81)

Accurate measurement of high voltages is required to guarantee the safe and stable operation of power systems. Modern power systems, which are mainly based on new energy sources, require high-voltage measurement instruments and equipment with characteristics such as high accuracy, wide frequency bandwidth, broad operating ranges, and ease of operation and maintenance. However, it is difficult for traditional electromagnetic measurement transformers to meet these requirements. To address the limitations of conventional Rydberg atomic measurement methods in low-frequency applications, this paper proposes an enhanced Rydberg measurement approach featuring high sensitivity and strong traceability, thereby enabling the application of Rydberg-based measurement methodologies under power frequency conditions. In this paper, a 110 kV high-voltage measurement method based on Rydberg atoms is studied. A power-frequency electric field measurement device is designed using Rydberg atoms, and its internal electric field distribution is analyzed. Additionally, a decoupling method is proposed to facilitate voltage measurements under multi-phase overhead lines in field conditions. The feasibility of the proposed method is confirmed, providing support for the future development of practical measurement devices. Full article

Electric submersible progressive-cavity pumps (ESPCPs) deliver high lifting efficiency but are prone to failure in the high-temperature, high-pressure, and multiphase down-hole environment, leading to production losses and elevated maintenance costs. To achieve reliable condition recognition under these noisy and highly imbalanced data constraints, we fuse deep residual feature learning, ensemble decision-making, and generative augmentation into a unified diagnosis pipeline. A class-aware TimeGAN first synthesizes realistic minority-fault sequences, enlarging the training pool derived from 360 field records. The augmented data are then fed to a CNN backbone equipped with ResNet blocks, and its deep features are classified by a Random-Forest head (CNN-ResNet-RF). Across five benchmark architectures—including plain CNN, CNN-ResNet, GRU-based, and hybrid baselines—the proposed model attains the highest overall validation accuracy (≈97%) and the best Macro-F1, while the confusion-matrix diagonal confirms marked reductions in the previously dominant misclassification between tubing-leakage and low-parameter states. These results demonstrate that residual encoding, ensemble voting, and realistic data augmentation are complementary in coping with sparse, noisy, and class-imbalanced ESPCP signals. The approach therefore offers a practical and robust solution for the real-time down-hole monitoring and preventive maintenance of ESPCP systems. Full article

The electric submersible pump (ESP) is a critical component in subsurface resource extraction systems, yet the presence of gas in the working medium significantly affects its performance. To investigate the impact of impeller perforation on gas–liquid mixing and internal flow characteristics, unsteady numerical simulations were conducted based on the Euler–Euler multiphase flow model. The transient evolution of the gas phase distribution, flow behavior, and liquid phase turbulent entropy generation rate was analyzed under an inlet gas volume fraction of 5%. Results show that under part-load flow conditions, impeller perforation reduces the amplitude of dominant frequency fluctuations and enhances periodicity, thereby mitigating low-frequency disturbances. Under design flow conditions, it leads to stronger dominant frequencies and intensified low-frequency fluctuations. Gas phase distribution varies little under low and design flow rates, while at high flow rates, gas accumulations shift from the midsection to the outlet with rotor rotation. As the flow rate increases, liquid velocity rises, and flow streamlines become more uniform within the channels. Regions of high entropy generation coincide with high gas concentration zones: they are primarily located near the impeller inlet and suction side under low flow, concentrated at the inlet and mid-passage under design flow, and significantly reduced and shifted toward the impeller outlet under high flow conditions. The above results indicate that the perforation design of ESP impellers should be optimized according to operating conditions to improve gas dispersion paths and flow channel geometry. Under off-design conditions, perforations can enhance operational stability and transport performance, while under design conditions, the location and size of the perforations must be precisely controlled to balance efficiency and vibration suppression. Full article

Enhanced or engineered geothermal systems (EGSs), or non-hydrothermal resources, are highly notable among sustainable energy resources because of their abundance and cleanness. The EGS concept has received worldwide attention and undergone intensive studies in the last decade in the US and around the world. In comparison, hydrothermal reservoir resources, the ‘low-hanging fruit’ of geothermal energy, are very limited in amount or availability, while EGSs are extensive and have great potential to supply the entire world with the needed energy almost permanently. The EGS, in essence, is an engineered subsurface heat mining concept, where water or another suitable heat exchange fluid is injected into hot formations to extract heat from the hot dry rock (HDR). Specifically, the EGS relies on the principle that injected water, or another working fluid, penetrates deep into reservoirs through fractures or high-permeability channels to absorb large quantities of thermal energy by contact with the host hot rock. Finally, the heated fluid is produced through production wells for electricity generation or other usages. Heat mining from fractured EGS reservoirs is subject to complex interactions within the reservoir rock, involving high-temperature heat exchange, multi-phase flow, rock deformation, and chemical reactions under thermal-hydrological-mechanical (THM) processes or thermal-hydrological-mechanical-chemical (THMC) interactions. In this paper, we will present a THM model and reservoir simulator and its application for simulation of hydrothermal geothermal systems and EGS reservoirs as well as a methodology of coupling thermal, hydrological, and mechanical processes. A numerical approach, based on discretizing the thermo-poro-elastic Navier equation using an integral finite difference method, is discussed. This method provides a rigorous, accurate, and efficient fully coupled methodology for the three (THM) strongly interacted processes. Several programs based on this methodology are demonstrated in the simulation cases of geothermal reservoirs, including fracture aperture enhancement, thermal stress impact, and tracer transport in a field-scale reservoir. Results are displayed to show geomechanics’ impact on fluid and heat flow in geothermal reservoirs. Full article

The present paper deals with a review on bearing currents in electrical machines, with major emphasis on mechanisms, impacts, and mitigation strategies. High-frequency common-mode voltages from the inverter-driven system have been found to be the main reason for bearing current leading to motor bearing degradation and eventual failure. This paper deals with bearing currents—electrical discharge machining (EDM) currents, circulating bearing currents, and rotor-to-ground bearing currents—and the various methods of their generation and effects that are harmful to the bearings and lubricants of a motor. Mitigation techniques, among which the following have been taken into account, are studied in this context: the optimization of PWM modulation, and the use of shaft grounding brushes, insulated bearings, and passive or active filters. Finally, advantages, limitations, and implementation challenges are discussed. A review comparing three-phase and dual three-phase inverters showed that, due to the increased degree of freedom in modulation strategies, it is possible to eliminate common-mode voltages through active modulation techniques. Such added flexibility will reduce the risk of bearing currents effectively. It also highlights future research directions in bearing current suppression, including the development of multi-phase motor systems, real-time monitoring technologies with artificial intelligence, and the use of new insulation materials for the enhancement of bearing reliability. The results obtained should guide future research and engineering practices in suppressing bearing currents to improve motor durability with high performance. Full article

The growing demand for higher reliability and efficiency in modern electric drives, coupled with the increasing adoption of multi-phase machines, has necessitated advancements in fault-tolerant control strategies. This paper presents a fault tolerance analysis for a six-phase permanent magnet synchronous machine (PMSM) connected to a five-level cascaded H-bridge converter, employing a level-shift pulse width modulation (LSPWM) technique. Unlike existing strategies, this work integrates a unique combination of three key innovations: first, a fault detection mechanism capable of identifying faults in both machine phases and inverter legs with high precision; second, an open-circuit fault compensation strategy that dynamically reconfigures the faulty inverter phase leg into a two-level topology to reduce losses and preserve healthy switches; and third, a modified closed-loop control method designed specifically to mitigate the adverse effects of short-circuit faults while maintaining system stability. The proposed approach is validated through rigorous simulations in Simulink and Hardware-in-the-Loop (HIL) tests, demonstrating its robustness and applicability in high-reliability applications. Full article

The paper presents a comprehensive overview of recent advancements in power electronics and electric machine design, focusing on novel topologies, semiconductor technologies, and integrated design techniques for electric drives. New drive topologies are gradually moving from the research phase to practical application, aiming to increase the rated power, efficiency, and reliability of electric drives. Specifically, these topologies can be categorized into series, which focus on increasing the operating voltage; parallel, which aim at enhancing the operating current and adding redundancy; and multiphase, known for offering significant benefits such as improved fault tolerance, higher torque generation, the possibility of synthetic loading, and diverse winding layout options. Emerging wide bandgap semiconductors, such as silicon carbide and gallium nitride, allow for operation at higher frequencies and lower power losses, enabling further drive integration. In terms of design practices, higher computational power, supported by advanced software, enables simulation and analysis in multiple domains (thermal, mechanical, electromagnetic) using multiphysics co-simulation, as well as multi-objective optimization concepts to achieve rapid prototyping of optimized drive systems. All the approaches described are important steps towards further improving electric drives for numerous applications in industry, consumer electronics, and transportation. Full article

Nowadays, electric propulsion system implementation in vehicles is popular, and many studies and prototypes have been accomplished in this field. Aircraft are important members of the vehicle family, and Unmanned Aerial Vehicles (UAVs) are part of this family as well. Some UAVs still have conventional propulsion systems, which are less efficient and are harmful to the environment. In addition, conventional systems are vulnerable to faults in their propulsion system components. To overcome these problems, we designed a multi-phase Brushless Direct Current (BLDC) motor, to achieve fault-tolerant operation. Our designed BLDC motor was implemented in a UAV model that was created on MATLAB Simulink, based on a currently used UAV. Our design and performance analysis are shown for the BLDC motor, both standalone and as implemented in the created UAV model. The electric propulsion system performance is shown, according to the determined flight profile. We observed that the designed electric machine is capable of producing the required torque to create thrust for lifting the UAV. There are some advantages and disadvantages to using the designed electric machine in this class of UAV. This is shown in the related sections. Full article

Small air-launched unmanned aerial vehicles (UAVs) face challenges in range and endurance due to their compact size and lightweight design. To address these issues, this paper introduces a multi-phase wind energy harvesting trajectory planning method designed to optimize the onboard electrical energy consumption during rendezvous and formation flight of air-launched fixed-wing swarms. This method strategically manages gravitational potential energy from air-launch deployments and harvests wind energy that aligns with the UAV’s flight speed. We integrate wind energy harvesting strategies for single vehicles with the spatial–temporal coordination of the swarm system. Considering the wind effects into the trajectory planning allows UAVs to enhance their operational capabilities and extend mission duration without changes on the vehicle design. The trajectory planning method is formalized as an optimal control problem (OCP) that ensures spatial–temporal coordination, inter-vehicle collision avoidance, and incorporates a 3-degree of freedom kinematic model of UAVs, extending wind energy harvesting trajectory optimization from an individual UAV to swarm-level applications. The cost function is formulized to comprehensively evaluate electrical energy consumption, endurance, and range. Simulation results demonstrate significant energy savings in both low- and high-altitude mission scenarios. Efficient wind energy utilization can double the maximum formation rendezvous distance and even allow for rendezvous without electrical power consumption when the phase durations are extended reasonably. The subsequent formation flight phase exhibits a maximum endurance increase of 58%. This reduction in electrical energy consumption directly extends the range and endurance of air-launched swarm, thereby enhancing the mission capabilities of the swarm in subsequent flight. Full article

New aerodynamic aircraft concepts enable the storage of volumetric liquid hydrogen (LH2). Additionally, the low temperatures of LH2 enable technologies such as the superconductivity of electrical fan drives and power distribution components. An increased power density of the onboard wiring harness and the electrical machine can be expected. The highest system efficiency and the smallest fuel and tank weight will be achieved with a highly efficient energy conversion by the fuel cell from LH2 to electrical energy. This publication shows a comprehensive study for cryogenic fan drives based on experimental-driven tape superconductor investigations, mission profile-based considerations, design analyses of superconducting electrical machines, and studies of the cooling concepts. A cryogenic system cannot be considered without a feasible cooling concept. Here, an approach with a safe He-based cooling system is proposed, using the LH2 flow to the fuel cell as a heat sink for the losses in the electrical system. Full article

In the realm of electric machines, there has been an increasing interest in multiphase (greater than three-phase) and hybrid excited machines. The benefits of multiphase machines include improved power density, efficiency, reliability, and fault tolerance, while for hybrid electric machines, the literature offers a variety of topologies, each with its own advantages and disadvantages. In essence, the term hybrid for electric machines is used when there is more than one source of excitation, e.g., permanent magnet (PM) excitation combined with or assisted by wound field (WF) excitation. This paper presents an extensive review of the latest topologies in hybrid machines. It explores fundamental principles, multiphase winding, and the advantage of multiphase over three-phase, as well as a comparison of ripple in the DC link for different numbers of phase winding. Additionally, this review discusses applications across industries, including automotive, aerospace, marine, and renewable energy systems. This paper later studies the motoric and generator modes of hybrid machines while considering the machine characteristics in both of these modes. Full article

The precise design of heat exchangers in automobile air conditioning systems for more sustainable electric vehicles requires an enhanced assessment of CFD mechanistic models for the subcooled boiling flow of pure eco-friendly refrigerant. Computational Multiphase Flow Dynamics (CMFDs) relies on two-phase closure models to accurately depict the complex physical phenomena involved in flow boiling. This paper thoroughly examines two-phase CMFD flow boiling, incorporating sensitivity analyses of critical parameters such as boiling closures, momentum closures, and population balance models. Three datasets from the DEBORA experiment, involving vertical pipes with subcooled boiling flow of refrigerant at three different pressures and varying levels of inlet liquid subcooling, are used for comparison with CFD simulations. This study integrates nucleate site density and bubble departure diameter models to enhance wall boiling model accuracy. It aims to investigate various interfacial forces and examines the S-Gamma and Adaptive Multiple Size-Group (A-MuSiG) size distribution methods for their roles in bubble break up and coalescence. These proposed approaches demonstrate their efficacy, contributing to a deeper understanding of flow boiling phenomena and the development of more accurate models. This investigation offers valuable insights into selecting the most appropriate sub-closure models for both boiling closure and momentum closure in simulating boiling flows. Full article

Artificial lift systems, such as electrical submersible pumps and sucker rod pumps, frequently encounter operational challenges due to high gas–oil ratios, leading to premature tool failure and increased downtime. Effective upstream gas separation is critical to maintain continuous operation. This study aims to predict the efficiency of downhole gas separator using machine learning models trained on data from a centrifugal separator and tested on data from a gravity separator (blind test). A comprehensive experimental setup included a multiphase flow system with horizontal (31 ft. (9.4 m)) and vertical (27 ft. (8.2 m)) sections to facilitate the tests. Seven regression models—multilinear regression, random forest, support vector machine, ridge, lasso, k-nearest neighbor, and XGBoost—were evaluated using performance metrics like RMSE, MAPE, and R-squared. In-depth exploratory data analysis and data preprocessing identified inlet liquid and gas volume flows as key predictors for gas volume flow per minute at the outlet (GVFO). Among the models, random forest was most effective, exhibiting an R-squared of 96% and an RMSE of 112. This model, followed by KNN, showed great promise in accurately predicting gas separation efficiency, aided by rigorous hyperparameter tuning and cross-validation to prevent overfitting. This research offers a robust machine learning workflow for predicting gas separation efficiency across different types of downhole gas separators, providing valuable insights for optimizing the performance of artificial lift systems. Full article

Due to their reliability, design and analysis models with PID and PID fuzzy controllers for six-phase drive are being applied in new areas in various industries, including transportation. First, the development of any system with multiphase motors requires an elaborate model to define the control mode and controllers. The modeling of a control system for six-phase drive is based on its conventional d-q mathematical model and indirect field-oriented control. In this study, a Simulink six-phase drive model is designed with indirect field-oriented control and simulated with two types of fuzzy controller, PID and PID fuzzy. The simulation results are presented and analyzed; these results reflect the step response and performance at the provided speed reference law while keeping the load application at a constant speed. A fuzzy controller with 49 rules is considered and applied. With field-oriented control and a well-tuned PID controller, the six-phase electric drive has good step response specifications: a short settling time when starting without a load, no overshoot in the step response, small size, and a slight decrease in speed when loaded. The system employing a PID fuzzy controller shows slightly better results in response to the application of torque: the decrease in speed is eliminated more quickly. The simulation results were tabulated with the PID and with the results of previous research that rearranged some models to only operate in the classical controller mode. The simulation results indicate the robustness to disturbance of both the systems with six-phase drive and provide high-quality transient specifications at the provided reference speed. Full article

Effective thermal management is essential for ensuring the safety, performance, and longevity of lithium-ion batteries across diverse applications, from electric vehicles to energy storage systems. This paper presents a thorough review of thermal management strategies, emphasizing recent advancements and future prospects. The analysis begins with an evaluation of industry-standard practices and their limitations, followed by a detailed examination of single-phase and multi-phase cooling approaches. Successful implementations and challenges are discussed through relevant examples. The exploration extends to innovative materials and structures that augment thermal efficiency, along with advanced sensors and thermal control systems for real-time monitoring. The paper addresses strategies for mitigating the risks of overheating and propagation. Furthermore, it highlights the significance of advanced models and numerical simulations in comprehending long-term thermal degradation. The integration of machine learning algorithms is explored to enhance precision in detecting and predicting thermal issues. The review concludes with an analysis of challenges and solutions in thermal management under extreme conditions, including ultra-fast charging and low temperatures. In summary, this comprehensive review offers insights into current and future strategies for lithium-ion battery thermal management, with a dedicated focus on improving the safety, performance, and durability of these vital energy sources. Full article