ABSTRACT Permanent magnet motors (PMMs) are a good choice for many applications due to their merits. These motors include synchronous motors (SMs) and flux modulation motors (FMMs). Their principles of operation depend on the air‐gap permeance harmonics. Permeance harmonics are one of the main factors influencing the performance characteristics of PMMs, including torque, back‐electromotive force (EMF), power factor, flux‐linkage, phase inductance, and flux‐weakening capability. This paper investigates the effect of air‐gap permeance harmonics on PMM performance. For this purpose, the winding function theory (WFT) and the Fourier series are used and various PMM structures having different effective permeance harmonics are presented. Since it is not possible to analyse all these structures, four structures of conventional PMMs are selected as representatives of all the structures. In this paper, the improved analytical modelling of WFT is used, in which the turn function is modified to include the saturation and slot effects. Also, it is possible to calculate the leakage inductance between two stator teeth. Ansys Maxwell software is applied to verify the analytical modelling. Finally, two designs of FMM with different air‐gap permeances are analysed and compared. The superior structure of this FMM is fabricated and tested to confirm the simulation results.
An improved active disturbance rejection controller (ADRC) suppression strategy is proposed to address the problem of broadband oscillation between the direct-drive wind turbine and the weak AC power grid. Firstly, the model of the direct-drive wind turbine connecting to grid is established, and the mechanism of broadband oscillation is analyzed. The ADRC design is conducted within the grid side converter. Secondly, a multi-objective optimization function is developed to tackle the difficulty of ADRC parameter tuning and improve system stability and response speed. The function includes the frequency error of the grid access and the adjustment time of the system. The parameter tuning of improved ADRC is realized by combining the method of global search and optimization to improve the rapidity, accuracy and rationality of the parameter design. Finally, MATLAB/Simulink simulations are used to compare the broadband oscillation suppression effects of controller parameters designed by the traditional bandwidth method with those from the proposed method. The overshoot, adjustment time, and harmonic content of the grid-connected current are reduced when the proposed method is applied. The results indicate that the improved ADRC strategy enables good dynamic response characteristics, noise immunity, and grid-connected current quality for the direct-drive turbine system.
Мета роботи. Узагальнити параметри оригінальної системи керування збудженням синхронних приводів для розповсюдження їх результатів на потужні виробничі комплекси, які працюють у режимах періодичних ударних навантажень, що сприятиме ліквідації аварійності через руйнування конструкції електромагнітної системи синхронних машин механізмів даного типу.
Методи дослідження. Для проведення досліджень використані положення теорії електричних машин, теорії автоматичного керування, методи розв’язання оптимізаційних задач із використанням математичного пакету MATHCAD, способи та методи моделювання у середовищі MATLAB складової SІMULINK.
Отримані результати. Шляхом вирішення оптимізаційної задачі отримано поліноміальні залежності рівнів форсування системи збудження синхронного привода із врахуванням величини поточного навантаження і штатними параметрами пружної муфти, а також визначені параметри ПІ-регулятора із уточненням коефіцієнту інтегральної ланки, що дозволяє уникнути надлишкової коливальності процесу накиду екстремального навантаження.
Наукова новизна. Враховуючи технологічні умови роботи автомат-стану ТПА-350 інструменту виготовлення цільнотягнутих труб, запропоновано оригінальний підхід та отримано поліноміальні залежності узагальнення основних параметрів керування системи збудження синхронного приводу, який працює у режимі періодичних екстремальних навантажень та показано перспективу використання даної системи у складі промислових збудників засобів живлення індукторних обмоток потужних синхронних приводів металургійних і дробарно-подрібнювальних механізмів.
Практична цінність. Отримані поліноміальні залежності головних параметрів системи керування збудженням потужних синхронних приводів дають можливість рекомендувати виробникам та проєктувальникам конкретні значення форсування, параметри ПІ-регулятора та задавача інтенсивності, що дозволить уникнути коштовних ремонтів і простоїв автомат-стану, які супроводжуються значними фінансовими витратами.
Мета роботи. Дослідження теплових процесів інвертора на базі IGBT модуля для застосування в перетворювачі частоти для керування роботою асинхронним двигуном.
Методи дослідження. Аналітико-розрахункові методи для аналізу теплових процесів інвертора на базі IGBT модуля.
Отримані результати. Дослідження теплових процесів інвертора SKM200GB12T4 на базі IGBT модуля було виконано за допомогою програми SemiSel. Розроблено математичну модель процесу охолодження інвертора SKM200GB12T4. Отримано залежність динамічного теплового імпедансу Zth(s-a) від часу, яка описується експоненціальною функцією. Розраховано значення сталої часу для цієї залежності, яка характеризує швидкість зміни температури охолоджувача, тобто якість його роботи. Теплова стала часу τ = 1,44 с показує час, необхідний для досягнення різниці температур » 63% від її стаціонарного значення. Таке низьке значення теплової сталої відображає ефективне охолодження завдяки високій швидкості повітряного потоку (7 м/с) та витраті повітря (426,43 м³/год), що є критично важливим для підтримки температури переходу IGBT нижче 175 °C під час перевантаження.
Отримано значення температурних максимумів інвертора при перевантаженні. Для перевантаження за 10,94 секунд максимальна температура для IGBT транзисторів становить 120.85 °C, а для діодів – 123.4 °С. Температура корпусу Тc = 71.21 °C та температура радіатора Тs = 63.56 °C залишаються однаковими для транзисторів та діодів і не перевищують граничну температуру роботи модуля завдяки стабільності системи охолодження. Але при більшому часі навантаження перегрів може зростати, що буде спричиняти деградацію напівпровідникових приладів.
Проведено дослідження процесів зміни температури і потужності при номінальному навантаженні і в режимі роботи при перевантаженні для одного періоду за допомогою програми SemiSel. Графіки зміни температури відображає стабільність температури в різних точках, таких як переходи IGBT транзисторів і зворотних діодів, завдяки ефективному тепловому контролю. Графік потужності показує циклічні зміни втрат, з піками у фазах, де струм і напруга максимальні. Ці дані підтверджують придатність модуля для використання в схемах управління.
Наукова новизна. На основі графічного аналізу кінетичних залежностей температури і потужності інвертора розроблено математичну модель процесу охолодження інвертора SKM200GB12T4, яка описує залежність динамічного теплового імпедансу Zth(s-a) від часу. Розрахована теплова стала часу для цієї залежності, яка характеризує швидкість зміни температури охолоджувача.
Практична цінність. Результати дослідження теплових характеристик інвертора SKM200GB12T4 можуть бути застосовані для оптимізації режимів роботи частотного перетворювача для керування роботою асинхронного двигуна.
To address the issues of slow processing speed and low accuracy when a large number of electric vehicles (EVs) are integrated into the power grid under vehicle-to-grid (V2G) scenarios, a dynamic EV classification and multi-step Markov chain aggregation method based on a density-based spatial clustering of applications with noise (DBSCAN) algorithm is proposed. In the classification phase, the DBSCAN algorithm is improved using the k-distance curve and its differential form, and the concept of incremental clustering is introduced to dynamically classify EV data, resulting in EV clusters characterized by multi-dimensional features such as state of charge (SOC), remaining connection time, and controllable capacity. In the aggregation phase, a multi-step state transition Markov chain theory is developed to construct online aggregation models for each EV cluster. This approach addresses the limitations of traditional Markov chains in handling multi-feature EV aggregation and improves the accuracy of the aggregated power output. Simulation results demonstrate that the proposed classification method can quickly and accurately partition large-scale EVs integrated into the grid into different clusters, and that the aggregation model significantly improves the accuracy of aggregate power estimation, effectively addressing the challenges associated with large-scale EV integration.
LFP batteries are widely used in the fields of electric vehicles and energy storage due to their advantages of high safety, long cycle life, and cost. However, lithium iron phosphate (LFP) batteries’ performance drops sharply in low temperatures (below 0 °C), with sudden capacity loss, increased internal resistance, charging difficulties, and lithium deposition risks, severely limiting their application in cold regions. To address the challenges posed by low temperatures, recent years have witnessed remarkable advancements in low-temperature LFP (LiFePO4) battery technology. The primary research areas encompass: material modification; innovations in electrolyte composition; morphology and techniques for element doping alongside precise control of particle dimensions. Recent advancements in battery technology have significantly enhanced the discharge capacity retention, charging acceptance, and cycling stability of LFP batteries in low-temperature environments. In the future, through multi-scale material design and interface engineering optimization, low-temperature LFP batteries are expected to achieve high-performance applications over a wider temperature range, further consolidating their mainstream position in the power and energy storage markets.
Chayakarn Saeseiw, Kosit Pongpri, Tanakorn Kaewchum
et al.
A multi-port conversion system that connects photovoltaic (PV) arrays, battery energy storage (BES), and an electric vehicle (EV) to a single-phase grid offers a flexible solution for smart homes. By integrating Vehicle-to-Grid (V2G) and Vehicle-to-Home (V2H) technologies, the system supports bidirectional energy flow, optimizing usage, improving grid stability, and supplying backup power. The proposed four-port converter consists of an interleaved bidirectional DC-DC converter for high-voltage BES, a bidirectional buck–boost DC-DC converter for EV charging and discharging, a DC-DC boost converter with MPPT for PV, and a grid-tied inverter. Its non-isolated structure ensures high efficiency, compact design, and fewer switches, making it suitable for residential applications. A state-of-charge (SoC)-based power management strategy coordinates operation among PV, BES, and EV in both on-grid and off-grid modes. It reduces reliance on EV energy when supporting V2G and V2H, while SoC balancing between BES and EV extends lifetime and lowers current stress. A 7.5 kVA system was simulated in MATLAB/Simulink to validate feasibility. Two scenarios were studied: PV, BES, and EV with V2G supporting the grid and PV, BES, and EV with V2H providing backup power in off-grid mode. Tests under PV fluctuations and load variations confirmed the effectiveness of the proposed design. The system exhibited a fast transient response of 0.05 s during grid-support operation and maintained stable voltage and frequency in off-grid mode despite PV and load fluctuations. Its protection scheme disconnected overloads within 0.01 s, while harmonic distortions in both cases remained modest and complied with EN50610 standards.
Uranium, extensively used in nuclear power generation, military applications, and scientific research, poses significant environmental and human health risks when released into soil due to its radiotoxicity and long half-life. Conventional remediation methods such as chemical leaching, stabilization, and bioremediation often face limitations including high costs, incomplete removal, prolonged treatment durations, and the potential for secondary pollution. In contrast, electrokinetic remediation (EKR) has emerged as a promising in situ technology for addressing uranium-contaminated soils, particularly in low-permeability environments where other methods are less effective. EKR operates by applying an external electric field across the soil matrix, inducing contaminant transport via mechanisms such as electromigration (ionic movement), electroosmosis (bulk fluid flow), and electrophoresis (movement of charged particles). These processes mobilize uranium species toward electrode zones, where they can be collected and removed through various treatment strategies. This review provides a comprehensive overview of recent advances in the application of EKR for uranium remediation, including fundamental transport mechanisms, system design parameters (e.g., electrode materials, electrolyte formulations, voltage gradients), and synergistic approaches such as coupling with phytoremediation and permeable reactive barriers. The role of numerical modeling in predicting system performance and optimizing operational parameters is also highlighted, along with the emerging potential of integrating renewable energy sources to enhance sustainability. Despite encouraging results at laboratory and pilot scales, challenges remain regarding scalability, energy efficiency, electrode longevity, and field deployment under heterogeneous site conditions. Future research should prioritize the development of hybrid systems, site-specific optimization strategies, and robust monitoring frameworks. Overall, EKR represents an environmentally friendly and technically viable solution for the remediation of uranium-contaminated soils, with considerable potential for application in nuclear facility decommissioning and long-term environmental restoration.
Abstract In the in‐service induction motors (IMs), friction and windage losses (FWL) value should be determined non‐intrusively. Hence, in the in‐service IMs, instead of measuring FWL, empirical equations are used to estimate FWL value. A novel technique is proposed for estimating the FWL value in low‐voltage three‐phase IMs based on obtained data from applying the no‐load test on 425 simulated IMs in the MATLAB software. The simulated IMs are 380 V, 50 Hz, with different numbers of poles in the power range of 0.37–400 kW. The FWL value for simulated IMs is calculated based on the IEEE 112 standard and by applying the no‐load test. Then, based on the dispersion of the obtained data from the no‐load test and using non‐linear regression, according to the number of IM poles for each number of poles, a third‐degree equation for FWL estimation is fitted to the test data. The proposed method to estimate the FWL value only needs the nominal output power listed on the IM nameplate. Also, unlike existing empirical relationships, the proposed approach estimates the FWL value for IMs with high accuracy and non‐intrusively. The effectiveness of the suggested technique is confirmed by simulation and practical results.
The escalating environmental concerns and energy crisis caused by internal combustion engines (ICE) have become unacceptable under environmental regulations and the energy crisis. As a promising alternative solution, multi-power source electric vehicles (MPS-EVs) integrate various clean energy systems to enhance the powertrain efficiency. The energy management strategy (EMS) is plays a pivotal role for MPS-EVs to maximize efficiency, fuel economy, and range. Reinforcement Learning (RL) has emerged as an effective methodology for EMS development, attracting continuous attention and research. However, a systematic analysis of the design elements of RL-based EMS is currently lacking. This paper addresses this gap by presenting a comprehensive analysis of current research on RL-based EMS (RL-EMS) and summarizing its design elements. This paper first summarizes the previous applications of RL in EMS from five aspects: algorithm, perception scheme, decision scheme, reward function, and innovative training method. It highlights the contributions of advanced algorithms to training effectiveness, provides a detailed analysis of perception and control schemes, classifies different reward function settings, and elucidates the roles of innovative training methods. Finally, by comparing the development routes of RL and RL-EMS, this paper identifies the gap between advanced RL solutions and existing RL-EMS. Potential development directions are suggested for implementing advanced artificial intelligence (AI) solutions in EMS.
Abstract This article presents a dual‐winding permanent magnet generator (PMG) system with integrated dual‐channel controller to meet the requirements of high power density, high reliability, and high output performance of aircraft electric power system. The dual‐winding of the PMG are designed to have the same phase spatially, with which the same rotor position can be applied in independent vector control. In addition, a dual‐channel controller is applied to control the two sets of windings, which achieves high‐performance control under normal state and fault‐tolerant control under fault state. The integrated dual‐channel controller integrates two sets of main power circuits into one controller and uses a main control unit, which simplifies the PMG system leading to reduction in the overall volume and weight. Reliability analysis of dual‐winding PMG system is proposed to be compared with that of the single‐winding PMG system. A dual‐winding cooperative control strategy and a fault‐tolerant control strategy are proposed to achieve high‐performance control of DC‐link voltage under normal condition and redundant functions under fault condition. As a result, the reliability of the PMG system is improved. The experimental results validate the effectiveness of the proposed PMG system and the control strategy.
Interior permanent-magnet synchronous machines (IPMSMs) are widely used as traction motors in electric drive-trains because of their high torque-per-ampere characteristics and potential for wide field-weakening operations to expand the constant-power range. This paper offers a categorization and a comprehensive overview of the control techniques applied to IPMSM drives in addition to presenting the necessary theoretical background. The basic concept, features and limitations, as well as the latest developments of the strategies, are summarized in the paper. This overview helps to lay the theoretical basis as well as to clarify the opportunities, challenges and future trends for controlling IPMSM drives for traction applications.
Discover a comprehensive set of tools and techniques for analyzing the impact of uncertainty on large-scale engineered systems. Providing accessible yet rigorous coverage, it showcases the theory through detailed case studies drawn from electric power application problems, including the impact of integration of renewable-based power generation in bulk power systems, the impact of corrupted measurement and communication devices in microgrid closed-loop controls, and the impact of components failures on the reliability of power supply systems. The case studies also serve as a guide on how to tackle similar problems that appear in other engineering application domains, including automotive and aerospace engineering. This is essential reading for academic researchers and graduate students in power systems engineering, and dynamic systems and control engineering.
Distribution system planning and operation has seen many structural changes due to the increased participation of consumers in the energy market and the adaptation of new technologies such as distributed energy resources (DERs), electric vehicles (EV) and local energy storage systems (ESSs). Despite the convenience of such technologies and the gradual drop in their prices, new technical challenges (e.g., excessive power losses) have emerged at the system level. Over the past few decades, power loss minimization in distribution systems has gained popularity and the need for loss sensitivity analysis (LSA) frameworks has become a necessity for its successful implementation. Existing work on LSA mostly focuses on system planning aspects through DER optimal placement and sizing. However, enabling LSA-based system operational applications is a vital step toward the successful transition to modern distribution systems (MDSs). Therefore, this paper presents a comprehensive overview on the state of the art in LSA for MDSs. First, the theoretical formulations of existing LSA methods are summarized. Then, the applications of LSA in distribution systems are highlighted. Finally, based on the analysis of literature, open research gaps and future research pathways are discussed.
CO2 mineralized all-solid waste alkali-activated cementitious materials can not only realize the storage of CO2 mineralized, but also shorten the curing cycle of alkali-activated cementitious materials and improve their compressive strength. It is a promising way of CO2 capture and utilization. The effects of the ratio of alkali-activated cementitious materials, mineralized curing pressure and mineralized curing time on the carbon fixation rate and compressive strength of CO2 mineralized cementitious materials were studied. The results show that the calcium carbide slag as alkali activator is more suitable for mineralization curing, and the sample with the highest Ca/Si ratio has the best carbon fixation ability under the same curing condition. Increasing the curing pressure and curing time of CO2 can improve the properties of the samples. Physical and chemical characterization test results show that, the microstructure of the mineralized samples is more compact than that of the natural curing samples, and the calcite-type calcium carbonate produced in the curing process is helpful to increase the compressive strength of the material. The research results provide basic data and reference for the development of CO2 mineralization curing technology of all-solid waste alkali-activated cementitious materials.
Applications of electric power, Production of electric energy or power. Powerplants. Central stations
Abstract Management and efficient operations in critical infrastructures such as smart grids take huge advantage of accurate power load forecasting, which, due to its non‐linear nature, remains a challenging task. Recently, deep learning has emerged in the machine learning field achieving impressive performance in a vast range of tasks, from image classification to machine translation. Applications of deep learning models to the electric load forecasting problem are gaining interest among researchers as well as the industry, but a comprehensive and sound comparison among different—also traditional—architectures is not yet available in the literature. This work aims at filling the gap by reviewing and experimentally evaluating four real world datasets on the most recent trends in electric load forecasting, by contrasting deep learning architectures on short‐term forecast (one‐day‐ahead prediction). Specifically, the focus is on feedforward and recurrent neural networks, sequence‐to‐sequence models and temporal convolutional neural networks along with architectural variants, which are known in the signal processing community but are novel to the load forecasting one.
Computational linguistics. Natural language processing, Computer software
Abstract The authors aimed to investigate the modulation behaviours and the interchangeability of three kinds of modulators in electrical machines, which are short circuited coil, salient pole reluctance and flux barriers, to understand the evolution of the modulator and reveal their individual action mechanism based on the general airgap field modulation theory. The modulation behaviours are systematically analysed and compared, including the modulation principles of the improved short circuited coil, the relationship between salient pole reluctance and pole arc together with slot opening depth etc., based on which the key rule of interchangeable modulators is summarised. Although different modulators possess different magnetic field modulation principles and magnetic conversion capabilities, they share the similar asynchronous behaviours and modulated harmonics distribution. In addition, the detailed topological analysis of traditional brushless doubly fed machine with interchangeable and combined modulators is presented to show the effectiveness of the theoretical investigation. Electromagnetic performances comparison, such as airgap flux density distribution, cross coupling ability, general torque performances and inductance characteristics, of a brushless doubly fed machine with different modulators are provided to reveal the relation between the machine performances and magnetic field conversion capability. Theoretical predictions are verified by 2‐D finite element analysis and experimental measurements.
Abstract A new semi‐analytical expression is presented based on two integrations for calculating the magnetic force of a solenoid inductor wound by rectangular cross‐section wire. The authors simplified the solenoid inductor coil to a collection of circular coils, and the current density of the coils in the radial direction which was inversely proportional to its radius is considered. The obtained expressions can be implemented by adaptive Gaussian quadrature integration with MATLAB programming. In addition, they used the filament method and the finite element method to calculate the magnetic force on the solenoid inductor coil. The correctness of the semi‐analytical expressions was verified by comparing the results of the semi‐analytical numerical method with those of the filament method and the finite element method, respectively. The derived semi‐analytical expressions of magnetic force allow a low computational time compared with the filament method and the finite element method to a specific accuracy. The calculation results show that: the solenoid inductor coil tends to compress in the axial direction, and the axial magnetic force on the outermost coils is the largest; the solenoid inductor coil tends to expand outward in the radial direction, and the radial magnetic force on the intermediate coil is the largest.