Browsing by Author "Vaimann, Toomas"

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  • AC Loss Analysis Approaches for Hairpin Winding Configuration: Analytical, Hybrid Model, and FEA
    (2023) Ghahfarokhi, Payam Shams; Kallaste, Ants; Podgornovs, Andrejs; Cardoso, Antonio J.Marques; Belahcen, Anouar; Vaimann, Toomas
     A4 Artikkeli konferenssijulkaisussa
    One of the effective options to achieve higher power density and lower-weight electric motors for electric vehicle (EV) applications is to replace the conventional winding with a hairpin configuration. This novel concept has several advantages, but the biggest drawback is high AC loss. Therefore, as this type of winding utilizes in EV motors for high-speed application, the correct estimations of this loss are essential during the design procedure. This paper presents three primary approaches to model and calculate the AC loss of hairpin windings: analytical, hybrid model, and FEA methods. In addition, the FEA method is used to validate and evaluate the accuracy of two other methods. Accordingly, both analytical and hybrid model results agree with FEA results. However, the hybrid model has higher accuracy rather than the analytical method.
  • AC Magnetic Loss Reduction of SLM Processed Fe-Si for Additive Manufacturing of Electrical Machines
    (2021-02-24) Tiismus, Hans; Kallaste, Ants; Belahcen, Anouar; Tarraste, Marek; Vaimann, Toomas; Rassõlkin, Anton; Asad, Bilal; Ghahfarokhi, Payam Shams
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Additively manufactured soft magnetic Fe-3.7%w.t.Si toroidal samples with solid and novel partitioned cross-sectional geometries are characterized through magnetic measurements. This study focuses on the effect of air gaps and annealing temperature on AC core losses at the 50 Hz frequency. In addition, DC electromagnetic material properties are presented, showing comparable results to conventional and other 3D-printed, high-grade, soft magnetic materials. The magnetization of 1.5 T was achieved at 1800 A/m, exhibiting a maximum relative permeability of 28,900 and hysteresis losses of 0.61 (1 T) and 1.7 (1.5 T) W/kg. A clear trend of total core loss reduction at 50 Hz was observed in relation to the segregation of the specimen cross-sectional topology. The lowest 50 Hz total core losses were measured for the toroidal specimen with four internal air gaps annealed at 1200 ◦C, exhibiting a total core loss of 1.2 (1 T) and 5.5 (1.5 T) W/kg. This is equal to an 860% total core loss reduction at 1 T and a 510% loss reduction at 1.5 T magnetization compared to solid bulk-printed material. Based on the findings, the advantages and disadvantages of printed air-gapped material internal structures are discussed in detail.
  • Additive manufacturing and performance of E-Type transformer core
    (2021-06-03) Tiismus, Hans; Kallaste, Ants; Belahcen, Anouar; Rassõlkin, Anton; Vaimann, Toomas; Ghahfarokhi, Payam Shams
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Additive manufacturing of ferromagnetic materials for electrical machine applications is maturing. In this work, a full E-type transformer core is printed, characterized, and compared in terms of performance with a conventional Goss textured core. For facilitating a modular winding and eddy current loss reduction, the 3D printed core is assembled from four novel interlocking components, which structurally imitate the E-type core laminations. Both cores are compared at approximately their respective optimal working conditions, at identical magnetizing currents. Due to the superior magnetic properties of the Goss sheet conventional transformer core, 10% reduced efficiency (from 80.5% to 70.1%) and 34% lower power density (from 59 VA/kg to 39 VA/kg) of the printed transformer are identified at operating temperature. The first prototype transformer core demonstrates the state of the art and initial optimization step for further development of additively manufactured soft ferromagnetic components. Further optimization of both the 3D printed material and core design are proposed for obtaining higher electrical performance for AC applications.
  • Additive Manufacturing of Prototype Axial Flux Switched Reluctance Electrical Machine
    (2021-03-22) Tiismus, Hans; Kallaste, Ants; Vaimann, Toomas; Rassõlkin, Anton; Belahcen, Anouar
     A4 Artikkeli konferenssijulkaisussa
    The fast-evolving additive manufacturing (AM) technologies are considered vital for the next industrial revolution as it is capable for cost-effective production of highly customizable complex components. Its freeform design and fabrication flexibility also suggest the production of embedded electromechanical components or even electrical machines with enhanced performance. Presently, due to the maturity of single-material additive manufacturing methods, prototyping of 3D printed electrical machines has taken the path of printing and assembling of individual highperformance machine components. This paper describes the design, the printing, the post-processing, the assembly and the controller of a printed prototype 4/6 axial flux switched reluctance electrical machine. The machine components were fabricated with selective laser melting system from 3 % silicon steel in a total print time of 57 hours. Commercially available bearings and conventional copper windings were added as part of the assembly.
  • Analysis of the Local and Global Forces Acting on the Coil Structure of a Modular Slotless Permanent Magnet Generator
    (2019-09) Kallaste, Ants; Vaimann, Toomas; Belahcen, Anouar; Ghahfarokhi, Payam Shams; Rassõlkin, Anton
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    This paper investigates the local and global forces acting on the coil structure of a low-speed modular permanent magnet generator for wind energy application. Two different configurations of the coil structure are studied. The first one consists of separately replaceable single-coil modules, whereas the second consists of three-phase coil-module assemblies. The purpose of the analysis is to investigate the advantages and disadvantages of each configuration in terms of vibrations and mechanical robustness. The investigations also provide the load for the mechanical analysis needed in the design of the retaining structure of the generator. The results show that there are strong fluctuations in the radial forces acting on the single-coil structure. The three-phase coil-module assembly reduces the fluctuations of the radial forces, but it results in an increase of the cogging torque, which is not suitable for the slotless design. Namely, the advantage of the slotless design is to reduce the cogging torque. The computed forces are then used in a structural mechanical simulation, the results of which are validated through strain measurements. The validation procedure is carried out on a specially built mock-up as accessing the generator on site is not possible.
  • Bearing fault analysis of bldc motor for electric scooter application
    (2020-12) Kudelina, Karolina; Asad, Bilal; Vaimann, Toomas; Belahcen, Anouar; Rassõlkin, Anton; Kallaste, Ants; Lukichev, Dmitry V.
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    In this paper, the bearing faults analysis of the brushless DC motor is presented. The research method is based on the analysis of the vibration signal of healthy as well as faulty bearings by the identification of specific frequencies on the vibration spectrum. For the experiment, the most common faults were inflicted on the bearings. As the used motor is intended for electric scooter applications, seven different damages were chosen, which are highly likely to occur during the scooter operation. The main bearing faults and the possibility of fault monitoring are addressed. The vibration data are gathered by the acceleration sensors placed on the motor at different locations and the spectrum analysis is performed using the fast Fourier transform. The variation in the amplitude of the frequency harmonics particularly the fundamental component is presented as a fault indicator.
  • Broken Rotor Bar Fault Detection Using Machine Learning: Optimal Frequency Resolution
    (2024-10-10) Koveshnikov, Semen; El Bouharrouti, Nada; Kudelina, Karolina; Naseer, Muhammad Usman; Vaimann, Toomas; Belahcen, Anouar
     A4 Artikkeli konferenssijulkaisussa
    This paper explores the optimal frequency resolution of the current spectra for detecting the broken rotor bar fault in induction motors with machine learning and motor current signature analysis. Conventional methods of broken rotor bar detection usually advocate for a higher frequency resolution in the motor current spectrum, which requires longer current signal measurements that are difficult and expensive to conduct. Thus, this work aims to identify the limitations to frequency resolution for successful broken rotor bar diagnosis when applying machine learning algorithms. The study also provides recommendations on the signal processing for feature extraction to enhance machine learning model performance. The machine learning algorithms used in the study are support vector machines, gradient boosting machines, and multilayer perceptron.
  • The cluster computation-based hybrid FEM–analytical model of induction motor for fault diagnostics
    (2020-11-01) Asad, Bilal; Vaimann, Toomas; Belahcen, Anouar; Kallaste, Ants; Rassõlkin, Anton; Naveed Iqbal, M.
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    This paper presents a hybrid finite element method (FEM)–analytical model of a three-phase squirrel cage induction motor solved using parallel processing for reducing the simulation time. The growing development in artificial intelligence (AI) techniques can lead towards more reliable diagnostic algorithms. The biggest challenge for AI techniques is that they need a big amount of data under various conditions to train them. These data are difficult to obtain from the industries because they contain low numbers of possible faulty cases, as well as from laboratories because a limited number of motors can be broken for testing purposes. The only feasible solution is mathematical models, which in the long run can become part of advanced diagnostic techniques. The benefits of analytical and FEM models for their speed and accuracy respectively can be exploited by making a hybrid model. Moreover, the concept of cloud computing can be utilized to reduce the simulation time of the FEM model. In this paper, a hybrid model being solved on multiple processors in a parallel fashion is presented. The results depict that by dividing the rotor steps among several processors working in parallel, the simulation time reduces considerably. The simulation results under healthy and broken rotor bar cases are compared with those taken from a laboratory setup for validation.
  • Cost-efficient real-time condition monitoring and fault diagnostics system for BLDC motor using IoT and Machine learning
    (2022) Raja, Hadi Ashraf; Raval, Hardik; Vaimann, Toomas; Kallaste, Ants; Rassolkin, Anton; Belahcen, Anouar
     A4 Artikkeli konferenssijulkaisussa
    A cost-efficient condition monitoring and fault diagnostic system are presented in this paper using the Internet of Things and machine learning. Most condition monitoring systems nowadays are either costly or used to monitor current values without emphasizing the analysis part. On the other hand, predictive maintenance of different electrical machines, including BLDC motors, is becoming the need of the hour. It reduces the cost needed for maintenance and can also be used to evade more significant faults in the machine. The data is transmitted in real-time using a data acquisition system onto the cloud, which is further processed to determine if there is a chance of any fault occurring in the motor. A short comparison of the results of different machine learning algorithms is also discussed related to predictive maintenance.
  • Custom Simplified Machine Learning Algorithms for Fault Diagnosis in Electrical Machines
    (2022) Raja, Hadi Ashraf; Asad, Bilal; Vaimann, Toomas; Kallaste, Ants; Rassolkin, Anton; Belahcen, Anouar
     A4 Artikkeli konferenssijulkaisussa
    With advancements in science, machine learning and artificial intelligence integration with different fields have opened up new horizons. In this paper, some simplified custom machine learning algorithms are defined to train different faults for electrical machines. The industry has been moving towards predictive maintenance of machines rather than scheduled maintenance with the new industry 4.0 revolution. It has also paved the way for researchers to explore more in machine learning and have specific machine learning training algorithms catered to diagnose faults in electrical machines. Here, three different variations of a simplified machine learning algorithm are present for the training of faults of electrical machines. A comparison of the results is presented at the end, along with further studies carried out in this area.
  • Design of a research laboratory drive system for a synchronous reluctance motor for vector control and performance analysis
    (2021-10-04) Heidari, Hamidreza; Rassõlkin, Anton; Kallaste, Ants; Vaimann, Toomas; Andriushchenko, Ekaterina; Belahcen, Anouar
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Motor-drive systems have the most significant share in industrial energy consumption, which requires a deep study in every aspect of the field. This paper presents a synchronous reluctance motor (SynRM) drive system based on Plecs RT box 1. The system’s design provides the op-portunity for the open-loop and closed-loop control of the motor and a characteristic performance analysis of the motor. This paper focuses on the hardware implementation of a research laboratory setup and the precise vector control of the SynRM in real-time. The application of the digital con-troller and inverter to drive SynRM is examined. The voltage, current, and speed transducers were employed for monitoring the protective measures and to control the motor in the closed-loop. The design of the signal conditioning and the intermediary cards for isolation and data acquisition are described in detail. An algorithm is proposed to measure the whole system parameters, including motor, inverter, and cables. Thanks to the RT box 1, the principle of real-time simulation of control algorithms is investigated, and the rapid control prototyping of field-oriented control (FOC) of SynRM was implemented. The simulation of the system was carried out in the Plecs platform, and the results are presented. The experimental results of the implemented control algorithms validate the setup’s performance and the control algorithm. Finally, as a study of the motor’s performance, the efficiency map of the motor is drawn in different speed and torque ranges.
  • Design optimization of permanent magnet clutch with Ārtap framework
    (2021-04-27) Andriushchenko, Ekaterina; Kaska, Jan; Kallaste, Ants; Belahcen, Anouar; Vaimann, Toomas; Rassõlkin, Anton
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    So far, Permanent Magnet (PM) clutches have been broadly used as torque transmission devices. With the aim of effective utilization of materials and energy in the manufacturing of PM clutches, design optimization has been widely applied. Generally, PM clutches are optimized applying linear dimensions as optimization parameters. On the contrary, optimization of PM clutch shapes has not been done extensively. Therefore, this paper performs optimization of PM clutch shapes with the following objectives: maximum tangential attraction force and minimum volume of utilized materials. To form optimal shapes, the points on the clutch surface are chosen as optimization parameters. The optimization is carried out using Ārtap framework in connection with COMSOL software, where the 3D model of the clutch has been created. After the optimization, the tangential attraction force has increased by 13 % and the volume of the clutch has been reduced by 24 %. Although the obtained shapes appear to be highly intricate, it does not pose an obstacle for modern manufacturing techniques.
  • Determination of Heat Transfer Coefficient for the Air Forced Cooling Over a Flat Side of Coil
    (2019-09) Ghahfarokhi, Payam Shams; Kallaste, Ants; Belahcen, Anouar; Vaimann, Toomas
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    The paper deals with the analytical and experimental determination of the forced convection heat transfer coefficients over the flat coil module. In the analytical part, the forced convection coefficients at different wind speeds are calculated based on various known equations of the forced convection heat transfer coefficient with unheated starting length. The experimental part presents the description of the test: loading the coil with DC current and measurements of the coil temperatures with thermal sensors while it was inside a wind tunnel. Based on the measurement, the convection coefficients were determined. In the final part, the experimental and analytical results are compared. It is found that the accuracy of the analytical results is more precise in highly turbulent flows.
  • Determination of heat transfer coefficient from housing surface of a totally enclosed fan-cooled machine during passive cooling
    (2021-06) Ghahfarokhi, Payam Shams; Podgornovs, Andrejs; Kallaste, Ants; Cardoso, Antonio J.Marques; Belahcen, Anouar; Vaimann, Toomas; Asad, Bilal; Tiismus, Hans
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    This paper presents the analytical calculation of the heat transfer coefficient of a complex housing shape of a Totally Enclosed Fan-Cooled (TEFC) industrial machine when it works below 20% of its nominal speed or close to stall. Therefore, passive cooling is dominant, and most of the heat is extracted by the combination of natural convection and radiation phenomena. Under these conditions, the area-based composite approach was used for the development of the analytical calculation method. A test rig using a TEFC Synchronous Reluctance Motor (SynRM) was constructed, and the collected experimental data was used to validate the proposed analytical method successfully.
  • Determination of heat transfer coefficient of finned housing of a TEFC variable speed motor
    (2020-11-10) Shams Ghahfarokhi, Payam; Kallaste, Ants; Podgornovs, Andrejs; Belahcen, Anouar; Vaimann, Toomas; Asad, Bilal
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    This paper proposes the analytical calculation of the heat transfer coefficient from the housing of a totally enclosed fan cooled (TEFC) machine during the active cooling. A particular focus is on the calculation of the heat transfer coefficient from the machine’s housing for different fan rotational speeds. The paper describes the challenges and provides solutions to dominate them during the analytical calculation of the heat transfer coefficient a TEFC electrical machine. Finally, the proposed method is validated experimentally on a totally enclosed fan cooled synchronous reluctance motor, and good correspondence between the analytical and experimental results is obtained.
  • Determination of natural convection heat transfer coefficient over the fin side of a coil system
    (2018-11-01) Ghahfarokhi, Payam Shams; Kallaste, Ants; Vaimann, Toomas; Rassolkin, Anton; Belahcen, Anouar
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    This paper presents a thermal study to define the appropriate correlations allowing the determination of the convective heat transfer coefficient over large parallel rectangular fins for a permanent magnet synchronous generator coil. For this purpose, an experimental setup is developed for both horizontal and vertical orientations and different input currents. The experimental results are compared with the analytical method, based on correlations proposed in the literature, which are generally limited for a small range of heat sinks. The results show that the analytical calculation based on Jone's correlation for the horizontal case and Tari's correlation for the vertical case, have good agreement with the experimental data. These correlations are experimentally validated for the calculation of the natural convection coefficients of large rectangular fins arrangement too.
  • Development of analytical thermal analysis tool for synchronous reluctance motors
    (2020-10-01) Ghahfarokhi, Payam Shams; Kallaste, Ants; Podgornovs, Andrejs; Belahcen, Anouar; Vaimann, Toomas
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    This study presents the principles of analytical lumped parameter model for a synchronous reluctance motor (SynRM) for traction application purposes. Particular focus is put on the calculation of the heat transfer from the machine's housing during the active and passive cooling. For this purpose, the area-based composite correlations method is proposed. The approach is attractive due to its simplicity and the fact that it closely models the temperature of the machine's housing. Finally, the proposed thermal model is evaluated experimentally on a totally enclosed fan cooled SynRM, and good correspondence between the analytical and experimental results is obtained.
  • Electrical resistivity of additively manufactured silicon steel for electrical machine fabrication
    (2019-06-01) Tiismus, Hans; Kallaste, Ants; Vaimann, Toomas; Rassõlkin, Anton; Belahcen, Anouar
     A4 Artikkeli konferenssijulkaisussa
    Additive manufacturing, commonly labeled as 3D printing is an essential component of the next industrial revolution, enabling both unprecedented fabrication freedom and streamlined production and logistics. Traditionally, the electrical machine cores are stacked from varnished soft magnetic laminations, which deliver reduced eddy and hysteresis losses during machine operation. Presently, dedicated metal printing platforms can produce industrial grade homo-material metal components, promoting the fabrication of machines with highly complex topologies, but also increasing the eddy current induced in these components, due to lack of laminated structure. In this paper, we present experimental resistivity measurement results of 3% and 6.5% silicon content steel fabricated with selective laser melting.
  • Hairpin Windings for Electric Vehicle Motors: Modeling and Investigation of AC Loss-Mitigating Approaches
    (2022-11) Ghahfarokhi, Payam Shams; Podgornovs, Andrejs; Cardoso, Antonio J. Marques; Kallaste, Ants; Belahcen, Anouar; Vaimann, Toomas
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    The hairpin winding configuration has been attracting attention as a solution to increase the power density of electric vehicle motors by enhancing the slot-filling factor. However, this winding configuration brings high AC losses during high-speed operation and we require new approaches to tackle this challenge. This paper considers reducing AC losses by proposing two main methods: correct transposition of conductors in parallel paths, and enhancing the number of conductor layers in a slot. First, the proper connection of conductors in parallel paths is considered, and the essential rules for this purpose are described. Next, the paper uses a numerical approach to deal with the effect of incorrect conductor transposition in winding paths on generating additional AC losses due to circulating currents. Finally, the impact of the number of conductor layers in the mitigation of AC losses is also discussed in detail. According to the results, by increasing the number of layers, ohmic losses in the layer near the slot opening dramatically decrease. For instance, ohmic losses in the layer near the slot opening of the eight-layer setup were 82% less than the two-layer layout.
  • Harmonic spectrum analysis of induction motor with broken rotor bar fault
    (2019-03-04) Asad, Bilal; Vaimann, Toomas; Kallaste, Ants; Belahcen, Anouar
     A4 Artikkeli konferenssijulkaisussa
    In this paper, the frequency spectrum of a three-phase induction motor's stator current on a linear scale is investigated. The broken rotor bar, spatial and grid fed harmonics are taken into consideration. Since the fundamental component of the power supply is always the most powerful component, it makes the spectrum less legible, increases the spectral leakage and makes the logarithmic scale inevitable. In this paper, a Chebyshev filter is used for attenuation of the fundamental component, because of its good transition band and no passband ripples. The current signals are taken from both simulation and laboratory environment and harmonics due to above-mentioned causes are segregated.