Electrical Machine Applications Research Articles

Improvement in mechanical as well as magnetic properties of a (FeCoNi)90Ti10-xAlx complex concentrated alloy series by tuning the chemical order

There is considerable interest in magnetic materials which also possess good mechanical properties. Hence, the effect of Ti/Al ratio on the microstructure, mechanical and magnetic properties of (FeCoNi)90Ti10-xAlx complex concentrated alloys (CCA) was investigated. An increase in the Ti/Al ratio in these CCA enhanced chemical ordering and substantially improved selected mechanical and magnetic properties. As the Ti/Al ratio changed from 10 to 0, the ductility increased from 7.5 to close to 50 %, the saturation magnetization (Ms) increased from 115.2 to 136.7 emu/g, and the coercivity (Hc) decreased from 17.9 to 4.2 Oe. The Fe30Co30Ni30Ti5Al5 alloy exhibit higher UTS×EL value than available soft magnetic materials and has relatively higher Ms and lower Hc compared with other CCA. These results provide a methodology to modulate the chemical order in the Fe-Co-Ni system by Al and Ti additions and synergistically tune the mechanical and magnetic properties for high performance rotating electrical machine applications.

Research on Predictive Speed Control Scheme for Surface-Mounted Permanent Magnet Servo Systems

In order to improve the dynamic response and disturbance rejection performance of electric machines, a deadbeat predictive speed control (DPSC) scheme for a permanent magnet synchronous motor (PMSM) is proposed. To begin with, a DPSC controller was proposed with the purpose of achieving precise control for the next control cycle, and the control parameters were determined based on the optimal parameter design method. For better application, performance comparisons were made with a conventional PI control, and the mismatch effects of inertia and torque were analyzed. In order to improve the disturbance rejection performance of the system, an extended sliding mode observer (ESMO) was constructed to compensate for disturbances. Experimental verification with a conventional PI control indicates that the proposed DPSC control can reduce the speed response time from 0.675 s to 0.650 s. When the electric machine operates stably and is applied to a torque disturbance of 0.4 Nm, the speed fluctuation and settling time can be reduced from 9 rpm and 1.7 s to 6 rpm and 0.5 s, respectively. This proposed method effectively enhances the speed control performance of PMSM and can be applied to high-performance electric machine applications.

Optimization of a damper system for noise and vibration reduction in a PMSM

PurposeThis paper aims to optimize passive damper system (PDS) design by configuring its parameters to improve its performance and behavior in permanent magnet synchronous machines (PMSM).Design/methodology/approachFirst, the principle and effectiveness of the PDS are recalled. Second, the impact of different PDS parameters on its operation is analyzed. Third, a multi-objective optimization is proposed to explore a compromise design of PDS. Finally, the transient finite element method simulation is performed to validate the optimized design, which can ensure an excellent noise reduction effect and weaker negative impacts.FindingsA suitable capacitance value in PDS is a key to realizing the damping effect. A larger copper wire can improve the noise reduction performance of PDS and reduce its Joule losses. A compromise solution obtained from a multi-objective optimization remains the excellent noise reduction and reduces Joule losses.Originality/valueThis paper explores the impact of PDS parameters on its operation and provides an orientation of PDS optimization, which is favorable to extend its application in different electrical machines.

State-of-Art Review of Renewable Energy-Based Systems for Electrical Machine Applications: Prospects and Challenges

Abstract Renewable energy sources (RES) are a game-changer since they produce no greenhouse gases (GHG). There is an increasing amount of interest in it across the world. The intermittent nature of RES makes it difficult to incorporate them into the existing power grid infrastructure and for use in electrical machines for industrial and domestic applications. As the number of RES grows along with different machine variants, innovative methods of interconnecting them are being explored. This study gives a thorough analysis of net zero RES (wind, solar and hydro) for electric machine applications considering their efficiency, feasibility, and reliability coupled with the trend of connection topologies. The Paradigm shift in material technology for RES application is also examined from the 1950s till the present paving the way for innovative design of novel electrical machines with optimal output performances and cost minimization. Modelling and optimization approaches were captured with the benefits and drawbacks highlighted. For electric machines to function at peak efficiency over time, energy harvesting from these sources becomes significant and must be controlled and maintained risk-free. In addition, the challenges, and prospects, associated with the operation of an Electric Machine technology in a clean environment have all been highlighted.

Innovative Design of Cooling System for a High-Torque Electric Machine Integrated with Power Electronics

The growth of electrical machine applications in high-torque environments such as marine propulsion and wind energy is encouraging the development of higher-power-density machines at ever higher efficiencies and under competitive pressure to meet higher demands. In this study, numerical simulations are performed to investigate the characteristics of air cooling applied to a 3 MW high-torque internal permanent magnet electric machine with integrated power electronics. The whole system of the main machine and two converters at either end are modelled with all details. Effects of different parameters on the total pressure drop and air flow rate to the machine and converters are examined. Results show that by changing the converter outlet hole size, the air flow rate to the machine and converter can be adjusted. Air guides and pin vents reveal excellent performance in the distribution of air to laminations and windings with a penalty of some increase in pressure drop, which is more pronounced when using smaller outlet holes. Furthermore, the air return manifold increases the pressure drop and causes a reduction in air flow rate to the converter. Insulation between compression plate and laminations is an unavoidable component used in electric machines and acts as a thermal insulator. However, it can also significantly augment pressure drop, especially in combination with smaller outlet holes. Thermal studies of the integrated power electronics illustrate that components’ temperatures are less than the temperature limit, confirming enough air through the converter. Analysis of power electronics in the case of fan failure provides the operational time window for the operators to respond.

Classifying the Percentage of Broken Magnets in Permanent Magnet Synchronous Motors Using Combined Short-Time Fourier Transform and a Pre-Trained Convolutional Neural Network

In critical applications of electrical machines, ensuring validity and safety is paramount to prevent system failures with potentially hazardous consequences. The integration of machine learning (ML) technologies plays a crucial role in monitoring system performance and averting failures. Among various motor types, permanent magnet synchronous motors (PMSMs) are widely favored for their versatile speed range, enhanced power density, and ease of control, finding applications in both industrial settings and electric vehicles. This study focuses on the detection and classification of the percentage of broken magnets in PMSMs using a pre-trained AlexNet convolutional neural network (CNN) model. The dataset was generated by combining finite element methods (FEMs) and short-time Fourier transform (STFT) applied to stator phase currents, which exhibited significant variations due to diverse broken magnet structures. Leveraging transfer learning, the pre-trained AlexNet model underwent adjustments, including the elimination and rearrangement of the final three layers and the introduction of new layers tailored for electrical machine applications. The resulting pre-trained CNN model achieved a remarkable performance, boasting a 99.94% training accuracy and 0.0004% training loss in the simulation dataset, utilizing a PMSM with 4% magnet damage for experimental validation. The model’s effectiveness was further affirmed by an impressive 99.95% area under the receiver operating characteristic (ROC) curve in the experimental dataset. These results underscore the efficacy and robustness of the proposed pre-trained CNN method in detecting and classifying the percentage of broken magnets, even with a limited dataset.

AC Losses in Windings: Review and Comparison of Models With Application in Electric Machines

AC Losses in Windings: Review and Comparison of Models With Application in Electric Machines

The Effects of the Unequal Rotor Slot Arc on Cogging Torque for Flux Switching Permanent Magnet Machines

Many of the electric machine researchers are studying the Flux switching permanent magnet (FSPM) machines. The cogging torque is one of the most unwanted parameter for highly sensitive electric machine applications. In this study, the configuration of the unequal rotor slot arc (URSA) to see the effects of the asymmetry for three phase FSPM machine has been studied. The proposed asymmetry contains of presenting different arc angled rotor poles and analyzing the torque performance of them by using 2D finite element analysis (2D-FEA). 12-stator pole/ 10-rotor pole (12s/10p) FSPM machine topology has been chosen for the design. Results proved that unequal rotor slot arc proposition demonstrate good performance in comparison to the symmetric design. Inequality on the rotor slots were simulated by using parametric analysis to minimize the cogging torque. The suggested design indicates a substantial reduction in cogging torque, achieving a conspicuous minimization. Consequently, the suggested using unequal rotor slot arc for FSPM machine has reasonable outcomes.

Experimental and Numerical Investigations on the Parameters of a Synchronous Machine Prototype with High-Temperature Superconductor Armature Windings

In their applications in electrical machines, high-temperature superconductors (HTSs) are mainly used as inductors in synchronous machines due to the AC losses which can lead to high cryogenic costs. In this work, we show the possibility of their use as armature windings, handling some precautions. The approach is based on the combined use of modeling and measurements. The construction and the preliminary tests of a handmade prototype of an axial field HTS synchronous machine are presented. Several tests have been conducted at liquid nitrogen temperature. The measurements have been confirmed by modeling results. The preliminary tests on the prototype, in both modeling and measurements, are very promising.

Designing and Commissioning an Experimental Setup to Evaluate AC Losses in Superconductors Under Transverse Rotating Fields

The development of low AC loss MgB <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> conductors and the increasing interest in a liquid hydrogen-based economy have reignited research into high power density fully superconducting (SC) electrical machines. In these machines, the armature winding experiences rotating fields that generate AC losses, making it essential to estimate these losses during machine design. While analytical and finite element analysis (FEA) models are available in the literature for estimating AC losses, these models for multi-filament MgB <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> superconductors have yet to be experimentally validated for machine operating regions. This paper presents a high-precision AC-loss test setup to measure AC losses in SC MgB <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> windings under rotating fields at the air-gap field, frequency, and operating temperature levels relevant to electrical machine applications. The experimentally measured AC losses are then compared with analytical and FEA models. Results demonstrate good agreement between measurements and predictions. The paper discusses the experimental setup, sample preparation, calibration, measurement method, and results. The study provides a significant contribution to the development of high power density fully SC electrical machines.

A Comprehensive Review and Experimental Investigation on Heat Pipes Application in Electrical Machines

The rapid development of transportation electrification brings unprecedented opportunities and challenges as well to the technological improvement of high-power density motors. As the major restriction of the motor performance, thermal issues attract more attentions recently and the heat pipe (HP), due to its high thermal conductivity and lightweight characteristics, is identified as a promising solution. Though HPs have been attempted in cooling systems of electrical machines, their thermal benefits still need to be fully understood. This article provides a comprehensive review and performs a series of experimental investigations to fill the technology gaps for the HP application in electrical machines. Firstly, the HP technology is briefly introduced, followed by a detailed review on its applications in different locations of electrical machines with corresponding thermal improvements reported. Then, experimental tests are conducted to investigate the correlation between the HPs’ parameters and their cooling effectiveness, including cross-sectional shape, bending angle, fins arrangement and inclination angle. The obtained results and conclusions could provide a guideline for the promotion of HPs in next generation electrical machines for future transportation.

Convolutional neural network guided prediction of saturation magnetic flux density of Fe-based metallic glasses

Fe-based metallic glasses (FeMGs) have recently garnered considerable research attention due to their unique characteristics, such as low core loss and high saturation magnetic flux density (Bs). They also have promising applications in modern electrical machines, such as inductors, motors, and transformers. For FeMGs with high Bs, a trial-and-error approach using various metalloid elements as constituents has been intensively carried out to consider satisfactory thermal stability. However, this approach is time-consuming and expensive because it requires a huge compositional space and results in a lack of understanding of metalloid effects on magnetic properties and thermal stability. In this study, we established a deep learning model using a convolutional neural network (CNN) based only on compositional descriptors of FeMG constituent elements to predict Bs as the representative magnetic property. In addition, an artificial neural network was applied with the same compositional descriptors for comparison, resulting in a lower prediction performance than that of the CNN model. The CNN model demonstrated high-performance metrics that included a determination coefficient (R2) of 0.960 and a low root-mean-square error of 0.067 T, indicating that the material composition-to-property map is well-defined. We further applied the CNN model to unseen datasets for Bs prediction and compared it with results reported in the existing literature. The predicted Bs values are in excellent agreement with the reported experimental results.

Структура и магнитные свойства порошков сплавов (Sm,Zr)(Co,Fe,Cu)z для магнитопластов

The hard magnetic (Sm,Zr)(Co,Fe,Cu)z alloys intended for the application as powder filler in bonded magnets are considered. The microstructure and intrinsic coercive force of the Sm0.87Zr0.13(Co0.702Cu0.088Fe0.210)6.7, Sm0.81Zr0.19(Co0.702Cu0.088Fe0.210)6.3, and Sm0.85Zr0.15(Co0.690Cu0.070Fe0.240)6.8 alloys, the structural and magnetic states of which were prepared at different aging temperatures and cooling rates, are studied. The formation of the high coercive force and adequate squareness of the magnetic hysteresis loop for alloy powders under study was observed at grain and subgrain sizes of the 2:17 phase of 10 – 20 μm. It is shown that the anisotropic powders of the Sm0.87Zr0.13(Co0.702Cu0.088Fe0.210)6,7 alloy can be prepared for manufacturing bonded magnets with a coercive force of 14 – 20 kOe and higher, which are intended for the application in electric machines.

Systematic Development of a Multi-Objective Design Optimization Process Based on a Surrogate-Assisted Evolutionary Algorithm for Electric Machine Applications

Surrogate model (SM)-based optimization approaches have gained significant attention in recent years due to their ability to find optimal solutions faster than finite element (FE)-based methods. However, there is limited previous literature available on the detailed process of constructing SM-based approaches for multi-parameter, multi-objective design optimization of electric machines. This paper aims to present a systematic design optimization process for an interior permanent magnet synchronous machine (IPMSM), including a thorough examination of the construction of the SM and the adjustment of its parameters, which are crucial for reducing computation time. The performances of SM candidates such as Kriging, artificial neural networks (ANNs), and support vector regression (SVR) are analyzed, and it is found that Kriging exhibits relatively better performance. The hyperparameters of each SM are fine-tuned using Bayesian optimization to avoid manual and empirical tuning. In addition, the convergence criteria for determining the number of FE computations needed to construct an SM are discussed in detail. Finally, the validity of the proposed design process is verified by comparing the Pareto fronts obtained from the SM-based and conventional FE-based methods. The results show that the proposed procedure can significantly reduce the total computation time by approximately 93% without sacrificing accuracy compared to the conventional FE-based method.

Performance-based design of pseudo-sliding mode speed control for electrical motor drives

Sliding mode control (SMC) is a powerful technique for nonlinear systems with high-performance requirements, such as machine drives with power converters. However, sliding mode controllers often present chattering, undesirable in these applications, due to the additional stress and switching losses. Smooth functions can replace the switching function to overcome this issue, with the addition of integral sliding manifolds for steady-state error elimination. Recent studies have investigated the stability of these control systems, without providing optimum tuning methods. This study offers a tuning method for the boundary layer limit for electrical machine applications, which grants the ripple-free solution with the smallest steady-state error. Experimental results of an induction machine variable speed drive show that the controller tuning by the proposed method met the design requirements and that SMC is a feasible method for control of the application mentioned above.

Manufacturing and Characterization of Novel Multilayer Magnets for Electrical Machine Applications

This paper presents the potentialities of diverse kinds of permanent magnet materials in order to build and characterize multilayer magnets, as well as to investigate their prospective application in electrical machines. In particular, bonded magnet and hybrid magnet powders are used to build two-layer samples, which pave the way for constructing special electrical machines with complex magnetic structures, such as the variable flux permanent magnet machines. In this study, samples of innovative double-layer magnets are built through a single press and the following magnetization procedure. A particular electromagnetic circuit is adapted to experimentally achieve the demagnetization characteristic to estimate the air gap magnetic flux behaviour in electrical machines. The measurement system flexibility allowed the testing of two double-layer magnets: the so-called parallel and series arrangements.

Plasma and Superconductivity for the Sustainable Development of Energy and the Environment

The main aim of this review is to present the current state of the research and applications of superconductivity and plasma technologies in the field of energy and environmental protection. An additional goal is to attract the attention of specialists, university students and readers interested in the state of energy and the natural environment and in how to protect them and ensure their sustainable development. Modern energy systems and the natural environment do not develop in a sustainable manner, thus providing future generations with access to energy that is generated from renewable sources and that does not degrade the natural environment. Most of the energy technologies used today are based on non-renewable sources. Power contained in fuel is irretrievably lost, and the quality of the energy is lowered. It is accompanied by the emissions of fossil fuel combustion products into the atmosphere, which pollutes the natural environment. Environmental problems, such as the production of gaseous and solid pollutants and their emission into the atmosphere, climate change, ozone depletion and acid rains, are discussed. For the problem of air pollution, the effects of combustion products in the form of carbon oxides, sulfur and nitrogen compounds are analyzed. The plasma and superconductivity phenomena, as well as their most important parameters, properties and classifications, are reviewed. In the case of atmospheric pressure plasma generation, basic information about technological gas composition, pressure, discharge type, electromagnetic field specification, electrode geometry, voltage supply systems, etc., are presented. For the phenomenon of superconductivity, attention is mainly paid to the interdependencies between Tc, magnetic flux density Bc and current density Jc parameters. Plasma technologies and superconductivity can offer innovative and energy-saving solutions for power engineering and environmental problems through decreasing the effects of energy production, conversion and distribution for the environment and by reductions in power losses and counteracting energy quality degradation. This paper presents an overview of the application of technologies using plasma and superconductivity phenomena in power engineering and in environmental protection processes. This review of plasma technologies, related to reductions in greenhouse gas emissions and the transformation and valorization of industrial waste for applications in energy and environmental engineering, is carried out. In particular, the most plasma-based approaches for carbon oxides, sulfur and nitrogen compounds removal are discussed. The most common plasma reactors used in fuel reforming technologies, such as dielectric barrier discharge, microwave discharge and gliding-arc discharge, are described. The advantages of solid waste treatment using plasma arc techniques are introduced. Applications of superconductors for energy generation, conversion and transmission can be divided into two main groups with respect to the conducted current (DC and AC) and into three groups with respect to the employed property (zero resistivity, ideal magnetism/flux trapping and quench transition). Among the superconductivity applications of electrical machines, devices for improving energy quality and storage and high field generation are described. An example that combines the phenomena of hot plasma and superconductivity is thermonuclear fusion. It is a hope for solving the world’s energy problems and for creating a virtually inexhaustible, sustainable and waste-free source of energy for many future generations.

Hybrid-Strand Winding Topology With Improved Power Density in Automotive Electric Machines

The rectangular profile conductor with a large cross section requires less slot space and has better heat dissipation ability than the traditional round profile one. But its application in automotive propulsion electric machines is thwarted by high ac winding losses and temperature rise under high-speed operations. This article proposes a novel stator winding topology with hybrid strands based on the ac losses' distribution characteristics and the theoretical relationship between the eddy current suppressing ability and the geometric parameters. The new winding can effectively reduce the ac loss and the peak temperature in the winding at high-speed operation. Meanwhile, it can maintain a high filling rate. Therefore, the machine's maximum rotating speed and power density can be effectively improved. In experimental validation, a winding sample with this new topology is manufactured and compared with the conventional one formed by rectangular wires. It shows the proposed method can reduce the winding ac loss by up to 12% and the temperature rise by 10–21%. It is validated to have considerable industrial potential in the future development of automotive motors.

Laser Additively Manufactured Magnetic Core Design and Process for Electrical Machine Applications

Additive manufacturing (AM) is considered the enabling technology for topology optimized components, with its unparalleled, almost free-form design freedom. Over the past decade, AM of electromagnetic materials has evolved into a promising new area of research. Considerable efforts have also been invested by the electrical machine (EM) research community to develop and integrate novel additive components. Several challenges remain, however, in printing soft magnetic flux guides—most prominently, reducing the induced eddy currents to achieve competitive AM core efficiency. This paper demonstrates the workflow of laser additive manufacturing magnetic cores with superior magnetic properties to soft magnetic composites (at 50 Hz excitation): describing the workflow, parameter tuning for both printing and annealing, and shape optimization. Process optimization yielded the optimal energy density of 77 J/mm3 and annealing temperature of 1200 °C, applied to prepare the samples with the highest relative density (99.86%), lowest surface roughness Rz (0.041 mm), minimal hysteresis losses (0.8 W/kg at 1.0 T, 50 Hz), and ultimate yield strength of 420 MPa. For Eddy current suppression, the sample (5 × 5 × 60 mm toroid) with bi-directional grading reached specific core losses as low as 1.8 W/kg (W10,50). Based on the findings, the advantages and disadvantages of AM graded cores are discussed in detail.

Machining of Zircaloy-2 using progressive tool design in EDM

ABSTRACT Zircaloy-2 is used in nuclear and biomedical industries therefore required high accuracy and precision, and achieved by application of electrical discharge machine (EDM). In this study, a new horizon of tool design is investigated for improvement in the performance of EDM. To measure the effect of tool design, Zircaloy-2 is machined with EDM using progressive Cu tool and measured the response parameters (MRR, TWR, radial overcut (Roc ), radial undercut (Ruc ), taper angle (Φ), and surface roughness). The progressive tool with varying design parameters of rake angle (0°, 45°, and 60°), flat land (2 mm), trunk diameters (10, 8, and 6 mm), and relief angle (0°, 45°, and 60°) are used to perform rough and finish machining in single EDM operation. MRR and SR are increased with increase in rake angle due to reduction in oxide and carbide deposition on the machined surface. Best combination for maximum MRR (1.131 × 10−3 mm3/min), minimum SR (4.313 µm), and minimum taper angle (2.17°) is obtained when machining is performed using T7. Multiresponse optimization (R-method) gives highest rank to progressive tool T7. Tool design improved TWR and significant reduction in radial overcut over conventional tool.