Electrical Machines Research Articles

Flow and Heat Transfer Characteristics in the Entry and Stabilized Flow Regions of a Circular Channel Rotating About a Parallel Axis

Abstract Cooling of heavy-duty electrical machines such as generators and motors is crucial for the smooth operations without thermal runaway. A commonly employed technique for the cooling of rotors in these machines is to place channels at different radial locations for the continuous passage of coolant. These channels are therefore rotating about a parallel axis, and the rotation-induced forces alter the flow and thermal behavior of the coolant compared to stationary channels. The present study reports a detailed numerical investigation on a long circular channel rotating about a parallel axis. The objective is to analyze the flow, heat transfer, and rotation-induced forces (Coriolis and centrifugal forces) in the entry region as well as in the region where flow is stable (the term ‘stable’ is used rather than ‘developed’ due to the presence of secondary flows in this region). The rotating channel was subjected to constant wall heat flux and constant wall temperature conditions at different Rotation numbers of 0, 0.15, 0.4, and 0.6. The Coriolis force is observed to be strong enough in the entry region to influence the flow. In the “stable flow” region, the centrifugal force becomes more dominant and forms counter-rotating secondary vortex pair, which causes circumferential variation in the Nusselt number. The flow and heat transfer characteristics for constant wall heat flux and wall temperature boundaries are the same for rotation conditions with similar values of rotational Grashof number. A correlation is presented for the circumferential variation of the Nusselt number in the stable flow region.

Alternative methodology of special coffee roasting in the electric popcorn maker

The aim was to develop and evaluate an alternative method for roasting coffee, using a domestic electric popcorn machine, estimating an ideal roasting time to obtain a drink of high quality. The experiment was conducted under laboratory conditions, with 10 treatments, with roasting times ranging from 3 to 8 minutes. Grain mass reduction and roasting color classification, according to the ABG Agtron scale, were evaluated. Roasting was carried out in a domestic electric popcorn maker, from Mondial brand, model PP-04, with a power of 1200W. Time intervals of five to six minutes showed better coffee characteristics, medium roasting point, ideal for specialty coffees. The use of the popcorn machine as a coffee roaster showed a satisfactory result, since in a short period of time, it provided a uniform roast, which attributes superior quality, compared to conventional coffee found on the market.

Unraveling the role of the BCC-B2 transition and V occupancies in the contradictory magnetism-ductility relationship of FeCoV alloys

The contradictory relationship between magnetism and ductility restricts further applications of FeCoV alloys in high-performance electrical machines. The role of the BCC-B2 transition, accompanied by vanadium (V) site occupancies, in magnetic moments and ductility has been explored using first-principles calculations. The variations in magnetism and ductility of FeCoV alloys are attributed to the coupling of the BCC-B2 transition and V occupancies. When V replaces Fe atoms in the equiatomic B2-FeCo alloy, the superior magnetism observed in B2-Fe50-cCo50Vc alloys is a consequence of the enhanced local magnetic moment of Fe and the ferrimagnetic-ferromagnetic transition in the magnetic state. Moreover, due to the preferential V occupancy in the B2 phase, the B2-Fe46Co50V4 alloy exhibits comparable ductility to the BCC-Fe50Co46V4 alloy. The results indicate that the increased brittleness in the B2 phase arises from the raised Peierls stress and the enhanced covalent component in interatomic bonding, which is caused by the strong hybridization between Fe and Co atoms. Pearson correlation analysis illustrates that valence electron concentration (VEC) and V content are significant factors in the contradictory relationship between magnetization and ductility. The theoretical results demonstrate that tuning the V content and atomic occupancies is helpful to achieve a trade-off between magnetization and ductility in B2-FeCoV alloys.

Interactive and educational simulation tool for permanent magnet synchronous machines

PurposeThis paper aims to present an interactive design and simulation tool for permanent magnet synchronous machines based on the finite-element-method. The tool is intended for education and research on electrical machines.Design/methodology/approachA coupling between the software MATLAB and finite element method magnetics is used. Several functionalities are included as modular scripts and represented in the form of a graphical user interface. Included are fully parametrized motor models, automatic winding generations and the evaluation of torque waveforms, core losses and speed-torque-diagrams. A survey was conducted to determine how the motivation of students concerning the covered topics is influenced by using the tool.FindingsDue to its simplicity and the intuitive visualization of the results, the tool provides direct access to the topic of electrical machines without having to deal with separate scripts. The modular structure of the software allows simple extensions with new functions. Because students can directly contribute to the tool with their own work, their motivation for using and extending it increases.Originality/valueThe presented tool offers more functionalities compared to similar free software packages, e.g. the calculation of core losses and speed-torque diagrams. Also, it is designed in such a way that it can be easily understood and extended by students.

State-of-the-Art Lightweight Implementation Methods in Electrical Machines

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.

Condition monitoring of electric vehicle motor testing machine’s Vital components using bagged trees and quadratic SVM: a comparative study

The future of the automotive industry lies in the utilization of electric vehicles (EVs). A crucial component of these EVs is the drive motor. The verification of critical parameters for the electrical motor is considered to be of utmost importance, and this is achieved through the use of a motor testing machine. The motor testing machine is utilized frequently to determine characteristic curve points and the electromagnetic behavior of electric motors under various conditions. However, it has been observed that the presence of a fault in the helical gear setup of the testing machine leads to frequent breakdowns and suboptimal performance, thereby affecting the efficiency of the assembly line in the production of electric vehicles. In light of these observations, the main objective of this research endeavor is to improve the motor test bench apparatus by altering essential design parameters through the utilization of vibration signal analysis and machine learning techniques. Prior to extracting statistical features, vibration signals are obtained at different gear settings. These signals are subsequently categorized using classifiers such as Bagged Trees and Quadratic SVM. Machine learning techniques are utilized to classify the gathered signals as either normal or faulty, both with and without the inclusion of a 0.25 KW load for each condition. The performance of multiple algorithms is evaluated and scrutinized. The results have demonstrated that the Bagged Trees technique outperforms the other algorithm, achieving an impressive accuracy of 95.3%. Consequently, the proposed method presents an adept solution for augmenting the motor test bench’s capability by modifying crucial design parameters.

LSTM-Autoencoder Deep Learning Model for Anomaly Detection in Electric Motor

Anomaly detection is the process of detecting unusual or unforeseen patterns or events in data. Many factors, such as malfunctioning hardware, malevolent activities, or modifications to the data’s underlying distribution, might cause anomalies. One of the key factors in anomaly detection is balancing the trade-off between sensitivity and specificity. Balancing these trade-offs requires careful tuning of the anomaly detection algorithm and consideration of the specific domain and application. Deep learning techniques’ applications, such as LSTMs (long short-term memory algorithms), which are autoencoders for detecting an anomaly, have garnered increasing attention in recent years. The main goal of this work was to develop an anomaly detection solution for an electrical machine using an LSTM-autoencoder deep learning model. The work focused on detecting anomalies in an electrical motor’s variation vibrations in three axes: axial (X), radial (Y), and tangential (Z), which are indicative of potential faults or failures. The presented model is a combination of the two architectures; LSTM layers were added to the autoencoder in order to leverage the LSTM capacity for handling large amounts of temporal data. To prove the LSTM efficiency, we will create a regular autoencoder model using the Python programming language and the TensorFlow machine learning framework, and compare its performance with our main LSTM-based autoencoder model. The two models will be trained on the same database, and evaluated on three primary points: training time, loss function, and MSE anomalies. Based on the obtained results, it is clear that the LSTM-autoencoder shows significantly smaller loss values and MSE anomalies compared to the regular autoencoder. On the other hand, the regular autoencoder performs better than the LSTM, comparing the training time. It appears then, that the LSTM-autoencoder presents a superior performance although it was slower than the standard autoencoder due to the complexity of the added LSTM layers.

Investigation of friction and vibration performance of lithium complex grease containing candle soot on aviation electrical machine

The prolonged operation of the motor in the all-electric aircraft can cause the fragmentation and shortening of grease thickener fibers, ultimately resulting in the lubricating grease becoming ineffective. In order to avoid grease failure causing motor winding burnout, this paper uses a four-ball friction testing machine to test the tribological properties of six composite greases containing candle soot with different concentrations, and analyzes the changes in friction coefficient and wear diameter. In addition, by building a test platform for motor vibration and noise, this paper studies the influence of lithium complex grease on vibration and noise characteristics of aviation electrical machine at different propeller speeds. The results show that the addition of 0.04 wt% candle soot lithium grease has the best tribological properties and vibration inhibition properties, because the candle soot in the oil film changes the sliding friction into rolling friction in the contact area of some friction pair. The temperature rise test of aviation electrical machine shows that the lithium complex grease plays an active role in the heat dissipation performance of the high-speed rotating motor.

Fabrication of high-entropy alloy superconducting wires by powder-in-tube method

High-entropy alloys (HEAs) are novel functional materials that exhibit excellent mechanical and chemical properties. Recent discovery of self-healing superconductivity of HEAs under ion irradiation suggests their great potential applications under extreme conditions such as in nuclear fusion reactors or space environments. Here, we report a fabrication of the HEA superconducting (SC) wires using the ex-situ powder-in-tube (PIT) technique for the first time, a crucial stepping stone to achieve various industrial and technological applications. The Ta1/6Nb2/6Hf1/6Zr1/6Ti1/6 HEA SC powder prepared by planetary ball milling was filled into Fe tubes, drawn into wires, and then sintered in evacuated quartz tubes at various temperatures. The HEA SC wire sintered at 700 °C for 1 h exhibits the highest critical current density (Jc) among the HEA SC wires sintered in the temperature range of 600 – 1000 °C. At 4.2 K, the Jc of this wire exceeds the common benchmark value of Jc = 100 kA cm−2, indicating the suitability of the HEA wire for large-scale applications, such as in high-field SC magnets. The SC transition temperature (Tc) of the HEA wire significantly increases from 5.10 K for the as-cast wire to 7.58 K with the sintering time (ts) of 30 min at 700 °C. The scaling of the flux pinning force as a function of the magnetic field indicates that normal point pinning plays a major role in achieving a high in-field Jc in HEA SC wires. These results underscore the significant potential of HEA superconductors for practical applications in high-field SC magnets, SC electric machines, and next-generation nuclear fusion reactors.

Stretch-forming characteristics of austenitic material stainless steel 304 at hot working temperatures

Abstract The need for sheet metal forming using highly resistant materials such as titanium alloys and stainless steel has increased recently. These materials possess elevated mean flow stress values, which make them difficult to draw at room temperature. To achieve a homogeneous distribution of strain in the stretched component, reduce the load required for plastic deformation, and greatly improve material formability, hot forming is helpful. The goal of the current study is to conduct stretch-forming experiments to investigate the forming characteristics of Austenitic material Stainless Steel (ASS) 304 at Hot working temperatures. Stretch forming experiments have been conducted on the Servo electrical sheet press test machine at 650 and 800°C. The formability has been estimated by constructing a Fracture forming diagram (FFLD), limiting the height of the dome (LDH) and the distribution of the strain of stretched cups. It has been discovered that the limit of forming bounds rises with the temperature reaching 800°C, while the DSA effect causes the necking region – the area between the safe and fracture limits ‒ to decrease with additional temperature rise from 800 to 900°C. Within the experimental limitations, it has been considered that the Hot forming of ASS 304 at 650°C gives the highest strain forming limits with a uniform strain distribution in the stretched cups. From the Formability limit diagram, dome height, and strain distribution, it can be observed that ASS 304 has good limiting strain up to 800°C with lower load application.

Electrical Machine Winding Performance Optimization by Multi-Objective Particle Swarm Algorithm

The present work aims to optimize the magnetomotive force and the end-winding leakage inductance from a discrete distribution of conductors in electrical machines through multi-objective particle swarm heuristics. From the development of an application capable of generating the conductor distribution for different machine configurations (single or poly-phase, single or double layer, integral or fractional slots, full or shortened pitch, with the presence of empty slots, etc.) the curves of magnetomotive force and the end-winding leakage inductance associated with the winding are computed. Taking as an optimal winding the one that presents, simultaneously, less harmonic distortion of the magnetomotive force and less leakage inductance, optimization by multi-objective particle swarm was used to obtain the optimal electrical machine configuration and the results are presented.

Sliding Mode Speed Control in Synchronous Motors for Agriculture Machinery: A Chattering Suppression Approach

Synchronous motors have extended their presence in different applications, specifically in high-demand environments such as agronomy. These uses need advanced and better control strategies to improve energy efficiency. Within this context, sliding mode control has demonstrated effectiveness in electric machine control due to its advantages in robustness and quick adaptation to uncertain dynamic system disturbances. Nevertheless, this control technique presents the undesirable chattering phenomenon due to the discontinuous control action. This paper introduces a novel speed integral control scheme based on sliding modes for synchronous motors. This approach is designed to track smooth speed profiles and is evaluated through several numeric simulations to verify its robustness against variable torque loads. This approach addresses using electric motors for different applications such as irrigation systems, greenhouses, pumps, and others. Moreover, to address the chattering problem, different sign function approximations are evaluated in the control scheme. Then, the most effective functions for suppressing the chattering phenomenon through extensive comparative analysis are identified. Integral compensation in this technique demonstrates improvement in motor performance, while sign function approximations show a chattering reduction. Different study cases prove the robustness of this control scheme for large-scale synchronous motors. The simulation results validate the proposed control scheme based on sliding modes with integral compensation, by achieving chattering reduction and obtaining an efficient control scheme against uncertain disturbances in synchronous motors for agronomy applications.

Detection of Inter-Turn Short Circuits in Induction Motors Using the Current Space Vector and Machine Learning Classifiers

Electric motors play a fundamental role in various industries, and their relevance is strengthened in the context of the energy transition. Having efficient tools and techniques to detect and diagnose faults in electrical machines is crucial, as is providing early alerts to facilitate prompt decision-making. This study proposes indicators based on the magnitude of the space vector stator current for detecting and diagnosing incipient inter-turn short circuits (ITSCs) in induction motors (IMs). The effectiveness of these indicators was evaluated using four machine learning methods previously documented in the literature: random forests (RFs), support vector machines (SVMs), the k-nearest neighbor (kNN), and feedforward and recurrent neural networks (FNNs and RNNs). This assessment was conducted using experimental data. The results were compared with indicators based on discrete wavelet transform (DWT), demonstrating the viability of the proposed approach, which opens up a way of detecting incipient ITSCs in three-phase IMs. Furthermore, utilizing features derived from the magnitude of the spatial vector led to the successful identification of the phase affected by the fault.

Ultra‐fast finite element analysis of coreless axial flux permanent magnet synchronous machines

AbstractLarge‐scale design optimisation techniques enable the design of high‐performance electric machines. Electromagnetic 3D finite element analysis (FEA) is typically employed in optimisation studies for accurate analysis of axial flux permanent magnet (AFPM) machines, which require extensive computational resources. To reduce the computational burden, a FEA‐based mathematical method relying on the geometric and magnetic symmetry of coreless AFPM machines is proposed to estimate the machine performance indicators using the least number of FEA solutions, thereby significantly lowering the running time. This method is generally applicable to AFPM machines with low saturation effects and cogging torque as exemplified for a printed circuit board (PCB) stator coreless AFPM machine. To further reduce the computation time, a systematically simplified equivalent 3D FEA model for planar PCB coils integrated with this machine is also proposed. The practical implementation of the introduced method is elaborated based on an example optimisation study, and an analytical method for fast design scaling is also discussed. The results of the proposed approach are compared with detailed transient FEA results, and a prototype 26‐pole PCB stator coreless AFPM machine was also used to validate the results experimentally.

Calculation of the parameters of an axial flux motor as an actuator of automotive systems

Problem. Axial flux electric motors offer several significant advantages compared to electric motors of traditional design. Currently, scientific periodicals contain numerous publications regarding the development and use of axial flux electric motors with printed windings across various fields. These include applications such as HDD-drives in computer technology, fans and pumps of various capacities, propulsion systems for bicycles and motorcycles, including in-wheel motors, manipulator drives for machine tools and industrial robots, and even within space technologies. Research confirms the high efficiency and size-to-weight ratios of axial flux motors when modern technologies are employed. However, there is little information available regarding the application of such motors in automotive electromechanical equipment. A distinctive feature of automotive electrical systems is their predominantly 12 V onboard power supply, along with high demands on size-to-weight ratios and reliability in conditions of elevated vibrations and wide temperature ranges. In this context, the development of an axial flux motor for automotive applications becomes relevant, particularly as an actuating mechanism for auxiliary systems such as window lifters, windshield wipers, air conditioning, and cooling fans, etc. Goal. The goal of the article is to determine the feasibility of using an axial flux electric motor as an actuator for automotive auxiliary systems by comparing its calculated parameters with the parameters of motors of traditional design using modern technologies and materials. Methodology. The methods and algorithms used for the calculation of electric machines take into account the characteristics and physical processes specific to axial flux machines with printed windings and permanent magnet arrays. Results. A comparison of the obtained characteristics of the designed motor with the characteristics of a modern prototype of traditional design was conducted. Based on the comparison, it was determined that the designed motor has better size-to-weight ratios while maintaining energy performance. Consequently, a conclusion was drawn about the feasibility of using electric motors with axial flux as actuators for automotive auxiliary systems. Originality. The prototype of the designed motor is considered to be a 250 W DC motor with a supply voltage of 12 V. The imposed constraint on the external diameter of the designed motor is set to 100 mm. Practical value. At the same output power and nearly identical torque, the calculated motor exhibits higher size-to-weight ratios. The weight of the calculated motor is 46% of the weight of the prototype. With an external diameter 54% larger than the prototype, the axial length of the calculated motor is 73% smaller. The mass of the calculated motor is 2.34 times smaller than the mass of the prototype.

Modeling, Control and Diagnosis of Electrical Machines and Devices

Nowadays, the increasing use of electrical machines and devices in more critical applications has driven the research in condition monitoring and fault tolerance [...]

Experimental platform for studying energy regeneration in electric vehicle powertrains

Investigation into the energy consumption in electric vehicles (EVs) plays a pivotal role in determining their autonomy and assessing the electric system performance across diverse operational scenarios. This study focuses on the concept of energy regeneration, encompassing the recovery and storage of kinetic mechanical energy during braking or descent in EVs. Employing control systems in power electronics becomes necessary to establish a seamless workflow across operational quadrants to ensure efficient energy regeneration in an electric machine functioning as both a motor and a generator. To seamlessly integrate new technologies into practical applications, it is essential to conduct thorough evaluations in laboratories prior to deployment. This paper introduces an experimental platform specifically designed to analyze energy consumption and storage in EVs by emulating their powertrains in a controlled laboratory environment. The platform comprises key components for emulating the powertrain of a single-motor electric vehicle with single-axle traction, including a power converter configured in two quadrants, an energy storage system, a primary rotating electric machine, and a mechanically coupled point load torque (another motor). This paper provides a detailed guide on implementing such a laboratory and for facilitating the testing of diverse motor technologies and controllers under varied operational conditions. This comprehensive approach allows for the assessment of electromechanical system efficiency, focusing on both energy recovery and comprehensive control of electric power converters. Validation tests conducted under urban conditions and on steep terrains demonstrate the effectiveness of the platform in analyzing the energy efficiency of both the induction machine and the power controller.

A versatilely high fidelity electric machines emulator for rapid testing of motor controller.

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.

Tuned Windings: the window of opportunity for the implementation of solid conductors in high frequency cryogenic electric machines

Optimization techniques can significantly improve the performance of electrical machines. The analysis and the optimization algorithms focus on computational efficiency. In this paper, the optimization of a high frequency electrical machine in cryogenic conditions is proposed. The losses introduced by AC current in a conductor are directly proportional with the applied frequency in terms of skin effect and proximity effect. The stator coil, made from two aluminium (Al) turns, in the presence of cryogenic coolants has been analysed at frequencies up to 1000 Hz. In order to reduce the AC losses introduced by the magnetic fields, Nonlinear Conjugate Gradient (NCG) method has been applied for the stator coil thickness optimization. Frequency dependence is observed in most simulations. In the presence of Liquid Hydrogen (LH2) coolant, Al 1100 conductor presents the minimum power loss.

The effect of elastic and plastic stresses on the electrical resistivity of conductive materials

The mobility sector has been responsible for large emissions of harmful greenhouse gases worldwide for years. E-mobility can contribute to a reduction of these emissions. For a faster spread and acceptance of electric vehicles, the achievable range and thus the efficiency of the individual components in the drive and charging train is essential. In addition to the battery and the electric machine, losses in the cables and bus bars are playing an increasingly important role. The cross-sectional shape, material and manufacturing technology of these conductive materials depends on the voltage and power to be transmitted and may still change in the future, especially in the field of fast charging and increased voltage.The aim of this work is to investigate the influence of the mechanical stress condition of copper, brass and aluminium materials on their electrical conductivity. The conductivity is measured by means of 4-wire measurements under defined tensile and compressive loads. The effects of elastic and plastic strains are taken into account. The findings can be used for an optimized manufacturing strategy for conductive components for future applications.