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Air transportation contributes significantly to harmful and greenhouse gas emissions. To combat these issues, there has been a recent emergence of aircraft electrification as a potential solution to mitigate environmental concerns and address fuel shortages. However, current technologies related to batteries, electric machinery, and power systems are still in the developmental phase to meet the requirements for power and energy density, weight, safety, and reliability. In the interim, there is a focus on the more electric and hybrid electric propulsion systems for aircraft. Hydrogen, with its high specific energy and carbon-free characteristics, stands out as a promising alternative fuel for aviation. This paper is centred on the application of hydrogen in aircraft propulsion, mainly fuel cell hybrid electric (FCHE) propulsion systems. Furthermore, application of hydrogen as a fuel for the aircraft propulsion systems is considered. A comprehensive overview of the hydrogen propulsion systems in aviation is presented with an emphasis on the technical aspects crucial for creating a more sustainable and efficient air transportation sector. Additionally, the paper acknowledges the technical and regulatory challenges that must be addressed to attain these goals. [Display omitted] • A comprehensive review of hydrogen propulsion systems for aviation is presented. • Key focus on PEMFC and SOFC systems for aircraft propulsion and auxiliary power. • Advances and challenges in hydrogen storage, water management, and fuel cell degradation. • State-of-the-art energy management strategies for fuel cell systems are discussed. • Future perspectives on hydrogen-powered aviation and necessary technological advancements. [ABSTRACT FROM AUTHOR]

The working environment and objects of agricultural machinery are different from those of automobiles, and agricultural machinery is greatly affected by such working environment and working conditions, while its power output system is more complex. Agricultural machinery not only has drive output, but also PTO output and hydraulic output, which together constitute the output system of agricultural machinery. Agricultural machinery conditions can be divided into road transportation working conditions and field operation working conditions. The working conditions of agricultural machinery can be divided into different load conditions according to the different traction tools and whether the hydraulic and PTO work, such as ploughing, rotary tillage, fertilization and transportation. Therefore, developing hybrid electric agricultural machinery systems that are suitable for various complex working conditions holds great theoretical significance and practical value. This should be done bearing mind the complex working conditions of agricultural machinery systems in agricultural work and the intricate challenges in designing hybrid agricultural machinery systems. In this paper, a two-dimensional matrix is used to represent the physical structure and dynamics of the multi-channel power output agricultural mechanism. A hierarchical two-dimensional matrix method for the generation and screening of hybrid electric agricultural machinery systems with multi-power output power is also proposed. The components of agricultural machinery are divided into an input layer and an output layer, and these components are coded and defined, and then transformed into a matrix. The hierarchical two-dimensional matrix method is used to generate and screen the hybrid electric agricultural mechanism type. Through the stratification of the matrix, complexity of the configuration generation is reduced, and the constraints are applied to the basic screening of the configurations generated. The rationality of the configurations obtained after generation and screening is verified by Simulink simulation. The results show that the configuration screened by this method can meet the performance requirements of agricultural machinery. [ABSTRACT FROM AUTHOR]

In 1752, the American polymath Benjamin Franklin supposedly flew a kite near the city of Philadelphia, Pennsylvania, to confirm that lightning had the same properties of common electricity that electrical machines produced and Leyden jars served to store. Illustrations, vignettes and paintings frequently portray the famous experiment, showing Franklin, with a boy, flying the kite in an open field and amid a storm. Nonetheless, little is known or said about the elements of these illustrations and the reference the illustrators used to portray the experiment. This paper aims to discuss these matters in a thoughtful study of seven nineteenth-century illustrations depicting Benjamin Franklin's kite experiment. I will show that the account by Joseph Priestley in his The History and Present State of Electricity, published in 1767, influenced these illustrations. I indicate that due to this influence, the illustrations present several departures from Franklin's original account, leading to a mistaken iconography of how the experiment took place. I conclude with a discussion on how this study can contribute to a better use and understanding of illustrations depicting scientific episodes in science classrooms. [ABSTRACT FROM AUTHOR]

The uniformity of the travel speed of electric reel sprinkling irrigation machines is a key factor affecting irrigation quality. However, conventional PID control is susceptible to sudden disturbances under complex farmland conditions, leading to reduced speed uniformity. To enhance the robustness of the control system, it is necessary to investigate new disturbance rejection control algorithms and their effects. Therefore, a kinematic model of the reel sprinkling irrigation machine and a brushless DC (BLDC) motor model were established, and a linear active disturbance rejection control (LADRC) strategy based on improved particle swarm optimization (IPSO) was proposed. The simulation results show that under variable speed conditions, the system exhibits no overshoot, with an adjustment time of 0.064 s; under variable load conditions, the speed vibration amplitude is less than 0.3%. The field test results indicate that at travel speeds of 10 m/h and 30 m/h, the maximum absolute deviation rate under IPSO-LADRC control is reduced by 27.07% and 13.98%, respectively, compared to PID control. The control strategy based on IPSO-LADRC effectively improves the control accuracy and robustness under complex farmland conditions, providing a reference for enhancing the control performance of other electric agricultural machinery. [ABSTRACT FROM AUTHOR]

This paper introduces a novel application of the inverse modelling method, which is designed to estimate core losses in both the stator and rotor regions of an electrical machine. The technique focuses on the use of short‐term transient temperature measurements obtained from the stator core of a slotless induction machine, with a focus on validating the measured temperature rise through a forward model. The measurement setup involves two primary approaches: (i) the use of thermal sensors embedded in a printed circuit board inside the stator core and (ii) surface sensors embedded on the stator yoke. Through the use of this innovative approach, the results indicate that the inverse modelling technique is highly effective in predicting core losses based on short‐time transient temperature rise measurements. [ABSTRACT FROM AUTHOR]

This article intends to propose a new concept of electric machines that works based on a category of magnetic fluids called "ferrofluids". For this purpose, a disc‐shaped rotor filled with ferrofluid material is employed instead of a common rotor of an axial‐flux machine, and the conceptual design of the new machine named here "axial‐flux ferrofluid electric machine (FFEM)" is presented. The operation principle of the FFEM is described and a dynamic‐transient model built on the d–q axes equivalent circuits is presented. Simulations are carried out by applying the given model in MATLAB and the results are investigated in different operating conditions. In order to identify the basic parameters and validate the simulation results, a prototype of the FFEM has been designed and manufactured, and some preliminary functional tests have been performed on the prototype. All simulation and experimental results indicate some distinguished excellent performances of the new machine. In the end, it can be stated briefly with some confidence that ferrofluid electric machines can have a high potential for future research and applications in various industries due to the simplicity of the structure, self‐starting capability, ability to work at a wide range of speeds and a flat torque profile. [ABSTRACT FROM AUTHOR]

The advent of Industry 4.0 has ushered in a new era of technological advancements, particularly in integrating information technology with physical devices. This convergence has given rise to smart devices and the Internet of Things (IoT), revolutionizing industrial processes. However, despite the push towards predictive maintenance, there still is a significant gap in fault prediction algorithms for electrical machines. This paper proposes a signal spectrum-based machine learning approach for fault prediction, specifically focusing on bearing faults. This study compares the effectiveness of traditional neural network algorithms with a novel approach integrating fuzzy logic. Through extensive experimentation and analysis of vibration spectra from various mechanical faults in bearings, it is demonstrated that the fuzzy-neuro network model outperforms traditional neural networks, achieving a validation accuracy of 99.40% compared to 94.34%. Incorporating fuzzy logic within the neural network framework offers advantages in handling complex fault combinations, showing promise for applications requiring higher accuracy in fault detection. While initial results are encouraging, further validation with more complex fault scenarios and additional fuzzy layers is recommended to fully explore the potential of fuzzy-neuro networks in fault prediction for electrical machines. [ABSTRACT FROM AUTHOR]

This paper discusses the construction and operating principle of an axial flux electric machine with hybrid excitation. Based on computer simulations using the Finite Element Method, an analysis was conducted with changes in the geometry of the magnetic circuit, which involves the rotation of the rotor disks relative to each other on the operating parameters of the machine. Both the generator state of operation, in the meaning of analyzing the induced voltage (adjustment at −11% ÷ +64%) and the cogging torque, and the motor state of operation, in the meaning of analyzing the ripple of the electromagnetic torque (possible reduction by almost 30%), were examined. The article concludes with observations on how the change in the angle of the rotor disks affects the efficiency of the disk machine with axial flux and hybrid excitation. [ABSTRACT FROM AUTHOR]

The Recent development of 2-DOF electrical machines leads to increasing need for 2-DOF position sensors. Using a planar sensor instead of two linear ones decreases the complexity, and cost of the employed drive. Therefore, in this paper a new slotless configuration is proposed for the planar resolver, that simplifies the manufacturing of the sensor. Then, the optimal combination of the stator/mover number of coils is determined based on the proposed analytical model. Finally, to reduce the number of integrated parts of the proposed resolver, a new configuration with skewed coils is proposed. The success of the developed model and the presented configuration is validated using three-dimensional finite element analysis. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The low-voltage electric machine (EM) is a core technology for transportation electrification, and features like high power density and compact volume are essential prerequisites. However, these requirements are usually in conflict with the reliability property of EM, especially in the safety-critical industry such as aviation. Therefore, an appropriate balance between high-performance and reliability needs to be found. Often, the over-engineering method is applied to ensure safety, although it might have a detrimental effect on the EM volume. To address this issue, the EM reliability assessment is included at the EM design stage through the physics of failure (PoF) theory. In EMs, the windings play a key role in electromechanical energy conversion, but their insulation system is subject to frequent failure and represents a reliability bottleneck. Therefore, in-depth research on the root causes of insulation breakdown is beneficial for EM reliability improvement purposes. Indeed, increasing awareness and knowledge on the mechanism of the insulation degradation process and the related lifetime modeling enables the growth of appropriate tools for achieving reliability targets since the first EM design steps. In this work, the main aspects of the insulation system, in terms of materials and manufacturing, are first reviewed. Then, the principal stresses experienced by the winding insulation system are deeply discussed with the purpose of building a profound understanding of the PoF. Finally, an overview of the most common insulation lifetime prediction models is presented, and their use for accomplishing the reliability-oriented design (RoD) and the remaining useful life (RUL) estimation are examined. [ABSTRACT FROM AUTHOR]

In high-speed electrical machines (HSEM), mechanical vibration associated with critical speeds of rotor systems can be detrimental to the machine operational stability, especially for vibration near resonances. The structural sizing of a rotor system is often constrained to its mechanical parameters, such as its overall weight, maximum torque, and rated power, which complicate the design, necessitating an iterative design optimization process. This work presents a systematic and iterative rotor structural sizing optimization methodology that incorporates semi-analytical and numerical modeling, specifically taking into account multiple mechanical design parameters from the static, rotordynamic, and electromagnetic-thermal evaluation. The proposed methodology provides an effective design optimization procedure for a general application of HSEM to accelerate its design process, by which the power density and the dynamics stability during high-speed operation are optimized simultaneously. A parametric analysis was carried out where a 24-kW, 12,000-rpm aviation starter-generator was optimized. It was demonstrated that the power density of the machine could be increased by 14.7% from 2.3 to 2.6 kW/kg, while the critical speed was increased by 128.6% from 1,400 to 3,200 Hz. [ABSTRACT FROM AUTHOR]

To meet the economy requirement of the horticultural machinery, a two-speed transmission system was proposed based on the characteristics of the driving cycle of the horticultural machinery. Firstly, the test cycle of the horticultural machinery was established based on the data collector that fixed on the machinery. Secondly, the two-speed driveline system was designed. To reduce the energy consumption in the horticultural machinery working cycle, the gear ratio of the two-speed gear box was optimized with the goal of minimum energy consumption by the Genetic Algorithm. The optimized gear ratio were 11.6 and 9.62. The comparison of energy consumption between single gear ratio and two-speed gear ratio was made. The comparison result showed that the energy consumption can reduce 0.25% under one transportation test condition, the energy consumption can reduce 0.41% under one ploughing test condition, and the energy consumption can reduce 0.41% under one rotary test condition. [ABSTRACT FROM AUTHOR]

Electric machines emulators (EMEs) based on hardware-in-the-loop (HIL), which effectively act as emulators to mimic the actual motor behavior of Interior Permanent Magnet (IPM) machines. EME is frequently used to evaluate motor controller and motor control methodologies prior to development. The inverse magnetization motor model, which is used as the basis for real-time simulation in this paper's proposal for an electric machine emulator system based on HIL, uses FEA to create the motor model data. The nonlinear features of the motor may be successfully replicated with this motor model, and the accuracy of the electric machine emulator can be enhanced by using a straightforward and trustworthy motor controller. The real-time simulation tool typhoon HIL is used in the study to develop a hardware-in-the-loop simulation platform for an IPM electric machines emulator. [ABSTRACT FROM AUTHOR]

The demand for high-power density motors has been increasing due to their remarkable output capability and compact construction. To achieve a significant improvement in motor power density, lightweight design methods have been recognized as an effective enabler. Therefore, extensive investigations have been conducted to reduce motor mass and achieve lightweight configurations through the exploration of lightweight materials, structures and manufacturing techniques. This article provides a comprehensive review and summary of state-of-the-art lightweight implementation methods for electrical machines, including the utilization of lightweight materials, structural lightweight design, and incorporation of advanced manufacturing technologies, such as additive manufacturing techniques. The advantages and limitations of each approach are also discussed in this paper. Furthermore, some comments and forecasts on potential future methodologies for motor lightweighting are also provided. [ABSTRACT FROM AUTHOR]

A new numerical procedure is presented to enable a hydrogen-fuelled two-stroke resonating free-piston generator target ideal Otto cycles to provide tracking paths for feedback control to maximise efficiency. Piston trajectories and design parameters are obtained for specified power, compression-ratio, and air-fuel-ratio. These parameters include scavenge port locations, heat release position, equivalent bottom-dead-centre position, and an electrical machine constant which is generally power-switched to take two values within a cycle. The main objectives of the paper are to develop the numerical procedure, and to demonstrate its use in finding a generator with maximum efficiency, and a generator with a single electrical machine constant, avoiding in-cycle power switching. To develop the procedure, a multi-physics generator model provides kinematics to an energy equation, culminating in a novel two-stage procedure. Stage-1 involves iteration and minimisation; Stage-2 just involves minimisation. Testing by simulation involves a 14-kW generator case study with compression ratio of 9, lean air-fuel equivalence ratio of 0.4, plus friction and electrical machine losses. An overall maximum generator efficiency of 54.9% is obtained using the procedure, compared to 51.3% without power switching. Computationally, the two-stage procedure proves highly efficient, typically taking around 11 min in total to complete on a desktop computer. The novelty of the procedure is its ability to optimally design and operate a hydrogen-fuelled resonating free-piston generator to meet a target specification, thereby offering a potentially inexpensive way to decarbonize transport, particularly in heavy duty applications. • Resonating free-piston generator is ideal energy converter for use with hydrogen. • New two-stage procedure able to target maximum efficiency. • Key cylinder positions and electrical machine constant easily found. • Planned Otto trajectories provide ideal two-stroke tracking paths. • New procedure tested on 14-kW generator maximises efficiency to 55%. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive review of mitigation approaches, with a specific focus on geometric modifications, to mitigate shaft voltage and bearing current in electric drives. While existing literature extensively covers inverter-based and coupling path-based methods, the potential of geometric modifications has been relatively underexplored. The geometric modification approach offers a cost-effective and weight-saving solution that can be incorporated during the early design phase of the machine. The review begins by outlining various mitigation techniques applied at the victim machine, including bearing insulation, ceramic ball bearings, shaft grounding, and more. Subsequently, it delves into the machine geometric modification approach, examining methods related to winding design, stator and rotor iron geometry, rotor surface insulation, and stator slot wedge modifications. The paper highlights the practical relevance of geometric modifications, emphasizing their advantages over conventional methods. The review paper aims to shed new light on the potential of geometric modifications in mitigating shaft voltage and bearing current in electric drives. By providing valuable insights into this approach, researchers and engineers can develop robust and efficient electric drive systems, advancing the field of electrical machine design and operation. [ABSTRACT FROM AUTHOR]

Environmental concerns have pushed toward electrified technologies for off‐road vehicle actuations that can lower greenhouse gas emissions and reduce energy consumption. Replacing a central diesel engine with a dedicated electric machine (EM) as a prime mover for the hydraulic supply offers several opportunities for so‐called ePumps (aka electric‐driven pumps) to maximize energy efficiency and limit the usage of electric materials. This paper discusses the impact of different choices for the ePumps architecture (i.e., fixed vs. variable displacement pump; variable speed vs. fixed speed electrical machine), and on their main design parameters in terms of size and efficiency. Although the procedure followed in the study could be extended to different types of electric and hydraulic units, the paper particularly considers ePumps based on permanent magnet synchronous machines combined with axial piston machines. The importance of properly considering the ePump drive cycle and its cooling requirements is taken into account while addressing energy efficiency, mass, and overall compactness of the solution. The results show that an ePump based on a variable displacement pump, when compared to fixed displacement ePumps, reduces the electrical machine size both in volume and mass up to 40%, when the high‐pressure demand is not combined with high flow rate demand, thus decreasing the cost of the EM. In all drive cycles, the variable speed EM–fixed displacement pump architecture has a higher efficiency, ranging from 1% to 5%, compared to the case of fixed speed EM–variable displacement pump. Finally, the paper compares the advantages and shortcomings of each ePump architecture presented, based on representative drive cycles. [ABSTRACT FROM AUTHOR]

Additively manufactured soft-magnetic components are inherently bulky leading to significant eddy current losses when applied to electrical machines. Prior works have addressed this issue by implementing structures based on the Hilbert space-filling curve which include eddy current suppressing gaps, thereby reducing the fill factor of the soft-magnetic component. The present research aims at investigating a number of space-filling curves in addition to sheets in order to find the optimal eddy current suppressing structure from an electromagnetic point of view. By means of both analysis and finite-element simulation, it was shown that sheets are superior at minimizing eddy current losses while space-filling curves excel at maximizing the fill factor. [ABSTRACT FROM AUTHOR]

In electrical machines, most of the iron loss estimation in finite element modeling is based on Bertotti coefficients obtained from the corresponding data sheet. However, often a more exact estimation of coefficients for the laminated steel material is needed. Especially in the case of high speed machines (where iron loss has the highest contribution to the total loss), it is very difficult to estimate the iron loss variation as a result of laser cutting when just using data sheet information as input data in finite element analysis. Laser cutting impacts also the magnetic properties, in terms of magnetization curves at different frequencies, not only the core losses. In this paper, three different core materials of the same lamination steel are prepared to realize the estimation of the Berttotti loss coefficient when the material is subjected to high frequency and under the stress of laser cutting. Experimental analysis is performed to obtain more precise values of Bertotti coefficients at a high frequency range so that they can be utilized in iron loss estimation in a high speed machine (100 krpm maximum speed-1667 Hz) which is further shown as an application. Finally, it is shown how frequency domain iron loss results can be utilized for the time stepping iron loss analysis. [ABSTRACT FROM AUTHOR]

Losses in electric machines produce heat and cause an efficiency drop. As a consequence of heat production, temperature rise will occur which imposes severe problems. Due to the dependence of electrical and mechanical performance on temperature, conducting thermal analysis for a special electric machine that has a compact configuration with poor heat dissipation capability is crucial. This paper aims to carry out the thermal analysis of an axial-field flux-switching permanent magnet (AFFSPM) machine for electric vehicle application. To fulfill this purpose, three-dimensional (3D) finite element analysis is performed to accurately derive electromagnetic losses in active components. Meanwhile, copper losses are calculated by analytic correlation in maximum allowable temperature. To improve thermal performance, cooling blades are inserted on the frame of AFFSPM, and 3D computational fluid dynamics (CFD) is developed to investigate thermal analysis. The effect of different housing materials, the external heat transfer coefficient, and various operating points on the components' temperature has been reported. Finally, 3-D FEA is used to conduct heat flow path and heat generation density. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is introduced in systems with electrical machines, such as in electric drive systems, wind energy generating systems, and small and special machines, to remote monitor and control the operation for data acquisition and analysis. These systems can integrate with the equipment and retrofit the existing installations. At the end of the control loops there are always motors, or actuators, of big or small ratings, of rotating or linear movements, electrical or nonelectrical, which must produce the motion. This article analyses selected aspects of research and applications of IoT-based control in electric drive systems and of wind energy conversion systems with induction machines. Various applications and study cases of control systems of electrical machines with IoT technology are described. With the IoT-based control of induction machine systems operators can remotely monitor parameters and obtain accurate real-time feedback during fast changing duty cycle operation. Thus, IoT creates multipurpose instruments in the remote control of induction machines. The paper offers a comprehensive analysis of IoT-based control applications in the field of induction machines, with technical details of design, construction, experimental testing, and prototyping, that are useful to energy engineering specialists in the sector of electric drives and wind energy conversion systems. [ABSTRACT FROM AUTHOR]

The main aim of this work is to present a step-by-step procedure to model and analyze the power loss distribution of three-level Gallium Nitride (GaN) inverters. It has been applied to three distinct three-phase three-level voltage source inverters utilized in electric traction drives: Active Neutral Point Clamped, Neutral Point Clamped and T-Type Neutral Point Clamped. The proposed analytical power loss modelling, combined with an equivalent representation of the electrical machine proved to be a viable solution to achieve a time-saving and low computational burden simulation platform, leading to satisfying accurate results. This has been confirmed by comparing the results carried out from the simulations of a 110 kW permanent magnet synchronous motor drive and those determined by considering a simplified circuital representation based on the proposed analytical power loss modelling. [ABSTRACT FROM AUTHOR]

An optimal electric machine design task can be posed as a constrained multi-objective optimization problem. While the objectives require time-consuming finite element analysis, constraints, such as geometric constraints, can often be based on mathematical expressions. This article investigates this mixed computationally expensive optimization problem and proposes a computationally efficient optimization method based on evolutionary algorithms. The proposed method always generates feasible solutions by using a generalizable repair operator and also addresses time-consuming objective functions by incorporating surrogate models for their prediction. The article successfully establishes the superiority of the proposed method over a conventional optimization approach. This study demonstrates how a complex engineering design task can be optimized efficiently for multiple objectives and constraints requiring heterogeneous evaluation times. It also shows how optimal solutions can be analysed to select a single preferred solution and harnessed to reveal vital design features common to optimal solutions as design principles. [ABSTRACT FROM AUTHOR]

This paper addresses the critical issue of fault detection and prediction in electric motor machinery, a prevalent challenge in industrial applications. Faults in these machines, stemming from mechanical or electrical issues, often lead to performance degradation or malfunctions, manifesting as abnormal signals in vibrations or currents. Our research focuses on enhancing the accuracy of fault classification in electric motor facilities, employing innovative image transformation methods—recurrence plots (RPs), the Gramian angular summation field (GASF), and the Gramian angular difference field (GADF)—in conjunction with a multi-input convolutional neural network (CNN) model. We conducted comprehensive experiments using datasets encompassing four types of machinery components: bearings, belts, shafts, and rotors. The results reveal that our multi-input CNN model exhibits exceptional performance in fault classification across all machinery types, significantly outperforming traditional single-input models. This study not only demonstrates the efficacy of advanced image transformation techniques in fault detection but also underscores the potential of multi-input CNN models in industrial fault diagnosis, paving the way for more reliable and efficient monitoring of electric motor machinery. [ABSTRACT FROM AUTHOR]

The extreme environmental issues and the resulting need to save energy have turned attention to the electrification of energy applications. One of the key components involved in energy efficiency improvements is the appropriate conception and manufacturing of electric machines. This paper overviews the electromagnetic analysis governing the behavior of permanent magnets that enable substantial efficiency gains in recent electric machine developments. Particular emphasis is given to modeling the properties and losses developed in permanent magnets in emerging high speed applications. In addition, the investigation of properties and harmonic losses related to ferromagnetic materials constituting the machine magnetic circuits are equally analyzed and discussed. The experimental validation of the implemented methodologies and developed models with respect to the obtained precision is reported. The introduction of mixed numerical techniques based on the finite element method intended to appropriately represent the different physical phenomena encountered is outlined and discussed. Finally, fast and accurate simulation techniques including aggregated lumped parameter models considering harmonic losses associated with inverter supplies are discussed. [ABSTRACT FROM AUTHOR]

The scope of the Conceive, Design, Implement, and Operate (CDIO) framework is to help the learner attain higher-order thinking skills (HOTS) in their courses. But most of the theory and practical courses offered in academic institutions are of a low-order thinking level. In outcome-based teaching and learning (OBTL), in order to achieve the graduate attribute of critical thinking, the learner needs to design and do the experiment and also be able to analyze and provide inferences about the data. Most laboratory courses offered in engineering colleges have an application level. To improve the course outcome from apply to analyze level, integrating a component of experiment analysis is required in the laboratory courses, which helps the students achieve higher-order thinking skills. An electrical laboratory course is given to the second semester students with the conventional experiments of machines at the application level. In order to inculcate analyzing skills, a case study of introducing a simple statistical analyzing tool based on MS-Excel in an experiment called 'load test on a 3-phase induction motor using variable frequency drive (VFD)' is presented in this paper. It was found from the laboratory assessment that the students using this analysis and visualization tool for interpreting the results scored well compared to the previous year's students. [ABSTRACT FROM AUTHOR]

The two related articles (GeoGebra Tool: Development of Applications for Electrical Machines and Drives Teaching Support and The Efficacy of GeoGebra Tool in Enhancing Electrical Machines and Drives Instruction) are parts of the unique and comprehensive research approach to improving university instruction of electrical machines and drives. The second part of this educational investigation presents the evaluative research on the applicability and quality of the described set of applications. The students of electrical power engineering assessed the quality of the developed EMD GeoGebra applications as very important and useful tools for learning and mastering related courses. Finally, the usefulness and effectiveness of these applications are summarised in the conclusion of the paper. [ABSTRACT FROM AUTHOR]

The paper reviews a set of developed GeoGebra applications designed to be used in several university courses related to Electrical Machines and Drives (EM D). The applications are developed to support students' learning of relatively complex physical phenomena iii the field through remote and online learning. A detailed review of the possibilities of newly developed applications in the field of electrical engineering and various types of electrical machines is presented in the Part I of the research. The emphasis is placed on the advantages of the applications and procedures for making conclusions based on the software possibilities in terms of learning process improvement. The presented developed EM D GeoGebra applications, adapted for different e-equipment, are publicly available. The Part H of this research presents the evaluative research on the applicability and quality of the described set of applications. The students of electrical power engineering assessed the quality of the EMD GeoGebra applications as very important and useful tools for learning and mastering related courses. Finally, the usefulness and effectiveness of these applications are summarised in the conclusion of the paper. [ABSTRACT FROM AUTHOR]

Copyright of Automatisierungstechnik is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the past decade, car manufacturers have started electrifying the traction chain of their vehicles. Although these vehicles attract more and more drivers, most of them have a limited range and are prohibitively expensive. Manufacturers must therefore offer high-performance conversion chains (particularly in terms of efficiency) while controlling costs. The power converter is a particularly crucial element of the conversion chains: it supplies the traction motor, and its structure and the way it is controlled can greatly influence the overall efficiency of the drive train. This paper studies two conversion structures that can be used as vehicle power converters, which are modeled and associated with an electric machine. The first is a classical three-phase inverter, and the second is a breakthrough architecture called IBIS (Intelligent Battery Integrated System). This battery integrates the conversion function directly into the battery, which reduces material costs. Two loss phenomena are also studied and modeled (with the help of finite element methods): iron losses in the electrical machine (magnetic losses in the ferromagnetic material used) and copper losses in the conductors (AC and DC losses in the conductors). The impact of the architecture is evaluated on a set of operating points from a road cycle standardized by the WLTP procedure. [ABSTRACT FROM AUTHOR]

The energy blockchain is a platform based on blockchain technology, creating a secure, transparent, and decentralized system for peer-to-peer transactions and automated smart contracts. This platform has the ability to facilitate the exchange and management of energy resources, such as electricity or renewable energy certificates. Our research aims to clarify the growth trends of energy systems with blockchain technology throughout the world. The novelty of this study is to understand the main factor in energy blockchain patent granting using a patent decomposition analysis and log mean Divisia index analysis and discover the relative importance in the R&D shift from electricity to other technology. Additionally, the IPC for energy blockchain technology primarily focuses on configuring and managing energy systems, including electricity, gas, and water supply. We also present a comprehensive overview of how countries and companies engage with energy blockchain technology and find China leads with 59% of patents, followed by the U.S. with 20%, but their specific tech shares differ. Participants span beyond traditional energy sectors, including electric and electronic machinery, IT firms, transport manufacturers, startups, and universities dedicated to blockchain technology. [ABSTRACT FROM AUTHOR]

Due to the growing pressure from governmental entities and customers in the European Union, Original Equipment Manufacturers are being pushed to design and manufacture sustainable and environmentally friendly products. A profitable industrial segment is expected to emerge from recycling end-of-life electric machines. This paper aims to identify an experimental synchronous reluctance machine with faulty copper windings to remanufacture the machine. The rewound design aims to achieve similar or improved characteristics and fit the novel requirements of the circular economy. The recyclability of the machine can be significantly increased by changing the copper windings to aluminum-based hairpin windings. The paper shows the geometrical, material, and winding identification plus finite element method-based analysis of the initial machine. The electric machine's slot-filling factor can be improved using an appropriate aluminum-based hairpin winding design compared to the original, even in the case of standard slots where the sides of the slots are not parallel. [ABSTRACT FROM AUTHOR]

The most common disadvantages of loss of excitation (LOE) impedance relay are its improper operation in the conditions of power system disturbances (PSD) and its long operation time. In this regard, to solve the mentioned problems and as a result improve the accuracy and speed of detecting the LOE events, four key variables including active power (Psg), reactive power (Qsg), load angle (δsg), and terminal voltage (Vsg) are selected, on the basis of an in‐depth theoretical‐ and simulation studies. These variables have been implemented in a precise combinational logic. In the developed LOE detection logic of this paper, the dependent parameters of Vsg and Qsg as well as Psg and δsg parameters are examined simultaneously in an AND logic cluster. If both the defined combinations detect the occurrence of LOE, the generator trip command is issued. Otherwise, the normal operation of the under‐study machine will continue. The results of the performed simulations in MATLAB/Simulink environment (2017b) during the detailed scenarios of LOE and PSD events on the IEEE 39‐bus standard system confirm the efficiency of the outlined LOE protection model. Meanwhile, its superiority from the viewpoints of accuracy, swiftness, and simplicity and cost of implementation are comprehensively compared with the other schemes. [ABSTRACT FROM AUTHOR]

Featured Application: The proposed braking intention identification control strategy has braking stability. As a widely-used construction machinery, the electric loader has the potential to recover braking energy due to its large mass and frequent starts and stops. Identifying braking intention accurately is the foundation of braking energy recovery. The typical braking condition of an electric loader is analyzed; the braking intention is divided into sliding brake, mild braking, moderate braking, and emergency braking. A large number of braking data were collected under different braking intentions, which are used as the basis for fuzzy control variable partitioning, fuzzy controller parameter setting and fuzzy control rule formulation. The control strategies of deceleration intention identification based on accelerator pedal, braking intention identification based on brake pedal and sliding brake intention identification are proposed in this paper, respectively. This paper takes the hydraulic brake pressure as a feedback parameter, even if there is hysteresis or failure based on the intention of pedal identification, the system can still provide sufficient braking strength to ensure the braking safety. The AMESim(R12)-Matlab/Simulink co-simulation model and prototype are built to verify the feasibility of the control strategy under different braking intention identification. The results show that the braking strength under stronger braking intention can satisfy the braking demand whether at a speed of 2 m/s or 12 m/s, which ensures the safety of emergency braking, and the electric loader can provide stable braking strength under different braking intention and different speed. This has good braking stability. [ABSTRACT FROM AUTHOR]

This article focuses on increasing the computational efficiency of 3D multi-static magnetic finite element analysis (FEA) for electrical machines (EMs), which have a magnetic field evolving in 3D space. Although 3D FEA is crucial for analyzing these machines and their operational behavior, it is computationally expensive. A novel approach is proposed in order to solve the magnetic field equations by exclusively using the magnetic scalar potential. For this purpose, virtual variable permanent magnets (vPMs) are introduced to model the impact of the machine's coils. The effect on which this approach is based is derived from and explained by Maxwell's equations. To validate the new approach, an axial flux machine (AFM) is simulated using both 2D and 3D FEA with the magnetic vector potential and current-carrying coils as a reference. The results demonstrate a high level of agreement between the new approach and the reference simulations as well as an acceleration of the computation by a factor of 15 or even more. Additionally, the research provides valuable insights into meshing techniques and torque calculation for EMs in FEA. [ABSTRACT FROM AUTHOR]

Three-dimensional printing is a promising technology that offers increased freedom to create topologically optimised electrical machine designs with a much smaller layer thickness achievable with the current, laminated steel-sheet-based technology. These composite materials have promising magnetic behaviour, which can be competitive with the current magnetic materials. Accurately calculating the iron losses is challenging due to magnetic steels' highly nonlinear hysteretic behaviour. Many numerical methodologies have been developed and applied in FEM-based simulations from the first introduced Steinmetz formulae. However, these old curve-fitting-based iron loss models are still actively used in modern finite-element solvers due to their simplicity and high computational demand for more-accurate mathematical methods, such as Preisach- or Jiles–Atherton-model-based calculations. In the case of 3D-printed electrical machines, where the printed material can have a strongly anisotropic behaviour and it is hard to define a standardised measurement, the applicability of the curve-fitting-based iron loss methodologies is limited. The following paper proposes an overview of the current problems and solutions for iron loss calculation and measurement methodologies and discusses their applicability in designing and optimising 3D-printed electrical machines. [ABSTRACT FROM AUTHOR]

We develop a novel methodology for the proxy variable identification of firm productivity in the presence of productivity-modifying learning and spillovers, which facilitates a unified internally consistent analysis of the spillover effects among firms. Contrary to the popular two-step empirical approach, ours does not postulate contradictory assumptions about firm productivity across the estimation steps. Instead, we explicitly accommodate cross-sectional dependence in productivity induced by spillovers, which facilitates identification of both the productivity and spillover effects simultaneously. We apply our model to study cross-firm spillovers in China's electric machinery manufacturing, with a particular focus on productivity effects of inbound FDI. [ABSTRACT FROM AUTHOR]