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Journal articles on the topic 'Modelling; induction machines; modelling'

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Published: 10 December 2022

Last updated: 28 January 2023

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1

Coates, C., D. W. J. Pulle, and A. Veltman. "Modelling of single phase induction machines." Australian Journal of Electrical and Electronics Engineering 1, no. 3 (January 2004): 151–56. http://dx.doi.org/10.1080/1448837x.2004.11464101.

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2

Slemon, G. R. "Modelling of induction machines for electric drives." IEEE Transactions on Industry Applications 25, no. 6 (1989): 1126–31. http://dx.doi.org/10.1109/28.44251.

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3

Raju, M. Naga, and M. Sandhya Rani. "Mathematical Modelling of Linear Induction Motor." International Journal of Engineering & Technology 7, no. 4.24 (November 27, 2018): 111. http://dx.doi.org/10.14419/ijet.v7i4.24.21868.

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The Linear Induction Motor is a special purpose electrical machines it produces rectilinear motion in place of rotational motion. By using D-Q axes equivalent circuit the mathematical modelling is done because to distinguish dynamic behavior of LIM, because of the time varying parameters like end effect, saturation of core, and half filled slot the dynamic modelling of LIM is difficult. For simplification hear we are using the two axes modelling because to evade inductances time varying nature it becomes complex in modelling, this also reduces number of variables in the dynamic equation. Modelling is done using MATLAB/SIMULINK. LIM can be controlled by using sliding model control, vector control, and position control.

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4

Ouadi, Hamid, Fouad Giri, and Luc Dugard. "Accounting for magnetic saturation in induction machines modelling." International Journal of Modelling, Identification and Control 14, no. 1/2 (2011): 27. http://dx.doi.org/10.1504/ijmic.2011.042337.

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5

Tenhunen, A., and A. Arkkio. "Modelling of induction machines with skewed rotor slots." IEE Proceedings - Electric Power Applications 148, no. 1 (2001): 45. http://dx.doi.org/10.1049/ip-epa:20010036.

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6

Kindl, Vladimir, Miroslav Byrtus, Bohumil Skala, and Vaclav Kus. "Key Assembling Issues Relating to Mechanical Vibration of Fabricated Rotor of Large Induction Machines." Communications - Scientific letters of the University of Zilina 21, no. 2 (May 24, 2019): 58–68. http://dx.doi.org/10.26552/com.c.2019.2.58-68.

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In many applications, where rotating machines of high power are used, high demands on reliability and safety are laid. Precise manufacturing procedures has to be kept even in case of machines retrofits when e.g. rotors are newly assembled. Even small inaccuracies or misguiding the precise technological procedure can lead to improper running of the machine and it can result in shut-down of complete drive. In case of primary circuits of nuclear power plants, it further means the shut-down of the whole power plant. Consequently, it results in significant financial losses (foregone profit and cost given by problem fixing). The paper presents a methodology of vibration origin investigation in case of large rotating machines which are part of drives like pump, compressors etc. The methodology is based on the detection of undesirable vibration using a diagnostic system on-site and further it uses mathematical modelling of corresponding mechanical parts to reveal the vibration origin. The modelling along with the measurement showed that the detected dangerous vibration is caused by misguided assembling of the rotor of the machine.

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7

Mekahlia, Abdelhak, Eric Semail, Franck Scuiller, and Hussein Zahr. "Reduced-Order Model of Rotor Cage in Multiphase Induction Machines: Application on the Prediction of Torque Pulsations." Mathematical and Computational Applications 25, no. 1 (January 29, 2020): 11. http://dx.doi.org/10.3390/mca25010011.

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For three-phase induction machines supplied by sinusoidal current, it is usual to model the n-bar squirrel-cage by an equivalent two-phase circuit. For a multiphase induction machine which can be supplied with different harmonics of current, the reduced-order model of the rotor must be more carefully chosen in order to predict the pulsations of torque. The proposed analysis allows to avoid a wrong design with non-sinusoidal magnetomotive forces. An analytical approach is proposed and confirmed by Finite-Element modelling at first for a three-phase induction machine and secondly for a five-phase induction machine.

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8

Terron-Santiago, Carla, Javier Martinez-Roman, Ruben Puche-Panadero, and Angel Sapena-Bano. "A Review of Techniques Used for Induction Machine Fault Modelling." Sensors 21, no. 14 (July 16, 2021): 4855. http://dx.doi.org/10.3390/s21144855.

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Over the years, induction machines (IMs) have become key components in industry applications as mechanical power sources (working as motors) as well as electrical power sources (working as generators). Unexpected breakdowns in these components can lead to unscheduled down time and consequently to large economic losses. As breakdown of IMs for failure study is not economically feasible, several IM computer models under faulty conditions have been developed to investigate the characteristics of faulty machines and have allowed reducing the number of destructive tests. This paper provides a review of the available techniques for faulty IMs modelling. These models can be categorised as models based on electrical circuits, on magnetic circuits, models based on numerical methods and the recently proposed in the technical literature hybrid models or models based on finite element method (FEM) analytical techniques. A general description of each type of model is given with its main benefits and drawbacks in terms of accuracy, running times and ability to reproduce a given fault.

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9

HARROUZ, Abdelkader, Fadila TAHIRI, Fatiha BEKRAOUI, and Ibrahim BOUSSAID. "Modelling and Simulation of Synchronous Inductor Machines." Algerian Journal of Renewable Energy and Sustainable Development 01, no. 01 (June 15, 2019): 8–23. http://dx.doi.org/10.46657/ajresd.2019.1.1.2.

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This study focuses on the study of the compartment of the synchronous inductor machine with variable speed, fed by a threephase inverter. Several transients were treated by simulation (start unloading, introducing a torque load, reversing and speed setpoint change). Then engine cushion at both loss and when starting without the damper. In addition, robustness tests on the parametric variation of (MSRB) were also performed. Based on the results of simulations, the control technique studied makes it possible to obtain good dynamic and static performances and has a robustness with respect to the external perturbation and the parametric variation.

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10

M S, Bhagyashree, and Mrs Raksha Adappa. "Modelling And Simulation Of An Induction Machine." IJIREEICE 4, no. 2 (April 11, 2016): 119–23. http://dx.doi.org/10.17148/ijireeice/ncaee.2016.24.

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11

Rogers, G. J., and D. Shirmohammadi. "Induction Machine Modelling for Electromagnetic Transient Program." IEEE Transactions on Energy Conversion EC-2, no. 4 (December 1987): 622–28. http://dx.doi.org/10.1109/tec.1987.4765901.

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12

Rogers, G. J., and D. Shirmohammadi. "Induction Machine Modelling for Electromagnetic Transient Program." IEEE Power Engineering Review PER-7, no. 12 (December 1987): 37–38. http://dx.doi.org/10.1109/mper.1987.5526837.

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13

Levi, E. "Main flux saturation modelling in double-cage and deep-bar induction machines." IEEE Transactions on Energy Conversion 11, no. 2 (June 1996): 305–11. http://dx.doi.org/10.1109/60.507182.

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14

Bottauscio, O., M. Chiampi, A. Manzin, and M. Zucca. "Prediction of losses in induction machines: a challenge for the modelling approaches." European Physical Journal Applied Physics 30, no. 1 (January 28, 2005): 7–16. http://dx.doi.org/10.1051/epjap:2005009.

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15

Herath, Herath Mudiyanselage Viraj Vidura, Jayashree Chadalawada, and Vladan Babovic. "Hydrologically informed machine learning for rainfall–runoff modelling: towards distributed modelling." Hydrology and Earth System Sciences 25, no. 8 (August 11, 2021): 4373–401. http://dx.doi.org/10.5194/hess-25-4373-2021.

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Abstract. Despite showing great success of applications in many commercial fields, machine learning and data science models generally show limited success in many scientific fields, including hydrology (Karpatne et al., 2017). The approach is often criticized for its lack of interpretability and physical consistency. This has led to the emergence of new modelling paradigms, such as theory-guided data science (TGDS) and physics-informed machine learning. The motivation behind such approaches is to improve the physical meaningfulness of machine learning models by blending existing scientific knowledge with learning algorithms. Following the same principles in our prior work (Chadalawada et al., 2020), a new model induction framework was founded on genetic programming (GP), namely the Machine Learning Rainfall–Runoff Model Induction (ML-RR-MI) toolkit. ML-RR-MI is capable of developing fully fledged lumped conceptual rainfall–runoff models for a watershed of interest using the building blocks of two flexible rainfall–runoff modelling frameworks. In this study, we extend ML-RR-MI towards inducing semi-distributed rainfall–runoff models. The meaningfulness and reliability of hydrological inferences gained from lumped models may tend to deteriorate within large catchments where the spatial heterogeneity of forcing variables and watershed properties is significant. This was the motivation behind developing our machine learning approach for distributed rainfall–runoff modelling titled Machine Induction Knowledge Augmented – System Hydrologique Asiatique (MIKA-SHA). MIKA-SHA captures spatial variabilities and automatically induces rainfall–runoff models for the catchment of interest without any explicit user selections. Currently, MIKA-SHA learns models utilizing the model building components of two flexible modelling frameworks. However, the proposed framework can be coupled with any internally coherent collection of building blocks. MIKA-SHA's model induction capabilities have been tested on the Rappahannock River basin near Fredericksburg, Virginia, USA. MIKA-SHA builds and tests many model configurations using the model building components of the two flexible modelling frameworks and quantitatively identifies the optimal model for the watershed of concern. In this study, MIKA-SHA is utilized to identify two optimal models (one from each flexible modelling framework) to capture the runoff dynamics of the Rappahannock River basin. Both optimal models achieve high-efficiency values in hydrograph predictions (both at catchment and subcatchment outlets) and good visual matches with the observed runoff response of the catchment. Furthermore, the resulting model architectures are compatible with previously reported research findings and fieldwork insights of the watershed and are readily interpretable by hydrologists. MIKA-SHA-induced semi-distributed model performances were compared against existing lumped model performances for the same basin. MIKA-SHA-induced optimal models outperform the lumped models used in this study in terms of efficiency values while benefitting hydrologists with more meaningful hydrological inferences about the runoff dynamics of the Rappahannock River basin.

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16

Taha Hussein, Hussein, Mohamed Ammar, and Mohamed Moustafa Hassan. "Induction Motors Stator Fault Analysis based on Artificial Intelligence." Indonesian Journal of Electrical Engineering and Computer Science 2, no. 1 (April 1, 2016): 69. http://dx.doi.org/10.11591/ijeecs.v2.i1.pp69-78.

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This article presents a method for fault detection and diagnosis of stator inter-turn short circuit in three phase induction machines. The technique is based on the stator current and modelling in the dq frame using an Adaptive Neuro-Fuzzy artificial intelligence approach. The developed fault analysis method is illustrated using MATLAB simulations. The obtained results are promising based on the new fault detection approach.

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17

M. S. Ferreira, Jossana, and Andrés Ortiz Salazar. "Bearingless Three Phase Induction Machine: Modelling And Driving." Eletrônica de Potência 12, no. 3 (November 1, 2007): 217–22. http://dx.doi.org/10.18618/rep.2007.3.217222.

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18

Benbouzid, M. E. H., M. Zerikat, and M. S. Naït-Saïd. "A practical approach to modelling induction machine saturation." European Transactions on Electrical Power 14, no. 2 (March 2004): 119–30. http://dx.doi.org/10.1002/etep.4450140206.

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19

Jannati, Mohammad, and Tole Sutikno. "Modelling of a 3-Phase Induction Motor Under Open-Phase Fault Using Matlab/Simulink." International Journal of Power Electronics and Drive Systems (IJPEDS) 7, no. 4 (December 1, 2016): 1146. http://dx.doi.org/10.11591/ijpeds.v7.i4.pp1146-1152.

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The d-q model of Induction Motors (IMs) has been effectively used as an efficient method to analyze the performance of the induction machines. This study presents a step by step Matlab/Simulink implementation of a star-connected 3-phase IM under open-phase fault (faulty 3-phase IM) using d-q model. The presented technique in this paper can be simply implemented in one block and can be made available for control purposes. The simulated results provide to show the behavior of the star-connected 3-phase IM under open-phase fault condition.

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20

Németh, Zoltán, and Miklós Kuczmann. "State space modeling theory of induction machines." Pollack Periodica 15, no. 1 (April 2020): 124–35. http://dx.doi.org/10.1556/606.2020.15.1.12.

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Abstract The paper discusses the theoretical background of the state space modeling of induction machines. The main goal is to present the necessary equations of the induction machine and the topic of the state space modeling. Although the induction machine is a highly non-linear system, LPV/qLPV model can be formulated from these equations.

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21

Riyaz, Ahmed, Pradip Kumar Sadhu, Atif Iqbal, and Md Abdullah Ansari. "Performance analysis of packed U-cell based inverter-fed five-phase induction motor drive using SINPWM technique." International Journal of Power Electronics and Drive Systems (IJPEDS) 11, no. 4 (December 1, 2020): 1899. http://dx.doi.org/10.11591/ijpeds.v11.i4.pp1899-1907.

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Induction motor is the backbone of current industrial applications. Multiphase machines can handle high power application easily. With the use of five-phase induction motor, advantage of both multi-phase and induction motor can be achieved. This paper presents analysis of five-phase seven level-based Induction motor system fed by packed U-cell based inverter. Modelling of five-phase induction motor is done with the help of mathematical equations using d-q axis transformation. Inverter voltage output comes to be approximately sinusoidal with 18.07% Total Harmonic Distortion (THD). Induction motor with specified parameters is simulated under no-load condition and attains steady state conditions after transient state.

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22

Sewell, P., K. J. Bradley, J. C. Clare, P. W. Wheeler, A. Ferrah, and R. Magill. "Efficient dynamic models for induction machines." International Journal of Numerical Modelling: Electronic Networks, Devices and Fields 12, no. 6 (November 1999): 449–64. http://dx.doi.org/10.1002/(sici)1099-1204(199911/12)12:6<449::aid-jnm365>3.0.co;2-w.

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23

Solcanu, V., M. Gaiceanu, M. Constantinescu, Ghe Samoilescu, and A. Sotir. "Modeling of Dispersion Magnetic Fields Developed by the Main Electromagnetic Systems Used on Military Ships." Scientific Bulletin of Electrical Engineering Faculty 20, no. 1 (April 1, 2020): 40–43. http://dx.doi.org/10.2478/sbeef-2020-0109.

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AbstractIn this paper, the authors present the modelling methods and numerical calculation of the dispersion magnetic field of electrical machines, as well as the results of their validation through practical measurements. An adequate analytic formula for magnetic induction calculation is proposed by the authors. The experimental results validate the proposed analytic model. Moreover, the proposed model is valid for both near and far field regions.

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24

Rolak, M., H. S. Che, and M. Malinowski. "Modelling and fault-tolerant control of 5-phase induction machine." Bulletin of the Polish Academy of Sciences Technical Sciences 63, no. 4 (December 1, 2015): 997–1006. http://dx.doi.org/10.1515/bpasts-2015-0113.

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Abstract The paper presents modeling and analysis of a 5-phase induction machine connected to 2-level 5-leg converter in case of open-phase failure. A control of the machine is accomplished using the Field Oriented Control with hysteresis current controllers. Moreover, a fault-tolerant algorithm is addressed and simulated.

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25

Le Roux, P. F., and M. K. Ngwenyama. "Static and Dynamic Simulation of an Induction Motor Using Matlab/Simulink." Energies 15, no. 10 (May 12, 2022): 3564. http://dx.doi.org/10.3390/en15103564.

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Industries are adequately configured with the operational devices that are required to develop induction motors. Engineers should precisely comprehend the kind of equipment that is constructed, as with every other production system, and should start by having the goal in their perspective. An adaptable simulation of an induction motor with a protective scheme is presented. The adaptable simulation assists engineers in accurately designing motors that meet all protective standards for certain purposes. This work achieved simulations of induction motors in stable and unstable conditions. An extensive study was performed to determine the optimum design of an induction motor. This paper attempts to provide engineers with a thorough grasp of the adaptable modelling of an induction motor. In this work, a direct dq0-direct axis algorithm is presented to implement both static and dynamic modelling of a three-phase induction machine due to possible faults and high-performance requirements in induction machines. The proposed algorithm was tested against several conventional methods, and it was observed that under the stable condition of the machinery, the proposed algorithm could remove any developing faults. This conserves time and minimises the labour required of the operator, which makes the proposed algorithm more efficient. Furthermore, the machine is demonstrated in a steady-state performance with respect to the current, active power, efficiency, reactive power, power factor, and speed when the torque loads range from 0 to 125% of its nominal torque. The transient behaviour of the machine was shown through the current, electromagnetic torque, electromagnetic torque versus speed, and speed under no-load, half-load (50%), and full-load (100%) conditions. Finally, the results of the proposed technique were compared to the results of the measured parameters. It was observed that when the load changed from a half load (50%) to a full load (100%), then the supply voltage was suddenly halved with the load at full load (100%). It was observed that the proposed algorithm provides accurate estimates with a deviation of not more than +/−2% from the measured parameters.

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26

Levi, E. "A unified approach to main flux saturation modelling in D-Q axis models of induction machines." IEEE Transactions on Energy Conversion 10, no. 3 (1995): 455–61. http://dx.doi.org/10.1109/60.464868.

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27

Ungku Amirulddin, U. A., G. M. Asher, P. Sewell, and K. J. Bradley. "Dynamic field modelling of torque and radial forces in vector-controlled induction machines with bearing relief." IEE Proceedings - Electric Power Applications 152, no. 4 (2005): 894. http://dx.doi.org/10.1049/ip-epa:20045233.

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28

Belhaj, M., P. Guérin, M. E. Zaïm, and L. Abdeljalil. "Influence of the frequential identification tests on the induction machine modelling." European Physical Journal Applied Physics 47, no. 3 (June 5, 2009): 31101. http://dx.doi.org/10.1051/epjap/2009099.

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29

Levi, E. "General method of magnetising flux saturation modelling in d–q axis models of double-cage induction machines." IEE Proceedings - Electric Power Applications 144, no. 2 (1997): 101. http://dx.doi.org/10.1049/ip-epa:19970781.

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30

Markovic, Nenad, Jeroslav Zivanic, Zoran Lazarevic, and Bratislav Iricanin. "The mathematical model for analysis and evaluation of the transient process of the three-phase asynchronous machine performance." Serbian Journal of Electrical Engineering 15, no. 3 (2018): 319–37. http://dx.doi.org/10.2298/sjee1803319m.

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This paper describes an adopted method which could be used in transient process modelling of three-phase asynchronous machines on the computer. Converter asynchronous electric machine feeding requires a detailed research of the transient process influence and the dynamic states of energy exchange between the electrical circuit feeding and the machine itself. A mathematical model has been formulated in order to solve the transient process of the three-phase asynchronous electric machine referring to the two asynchronous machines and containing two matrix models defined by Park?s d - q components. In the system of symmetrical components the state and the operation of the first machine was defined based on relations and operation conditions of a direct sequence system and of other machines based on relations and operation conditions of an inverse sequence system. The new method has been derived from the existing psbpwm MATLAB package. The new model simulates the state and operation of a single machine with identical parameters through the state and operation of the two machines with identical parameters: the first in a direct sequence system and the others in an inverse sequence system. Operation analysis of the three-phase induction machine is limited to a transient process occurring in the right angled shape of voltage feeding. The new presented model can, with certain limitations, be applied not only to a three-phase asynchronous machine model but to other alternating current machines which have a stator and a rotor. The experiment has been performed following an example of asymmetrical feeding followed by inverse component phenomena of electrical and mechanical values in the machine.

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31

Hussein, H. A. Taha, M. E. Ammar, and M. A. Moustafa Hassan. "Three Phase Induction Motor's Stator Turns Fault Analysis Based on Artificial Intelligence." International Journal of System Dynamics Applications 6, no. 3 (July 2017): 1–19. http://dx.doi.org/10.4018/ijsda.2017070101.

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This article presents a method for fault detection and diagnosis of stator inter-turn short circuit in three phase induction machines. The technique is based on modelling the motor in the dq frame for both health and fault cases to facilitate recognition of motor current. Using an Adaptive Neuro-Fuzzy Inference System (ANFIS) to provide an efficient fault diagnosis tool. An artificial intelligence network determines the fault severity values using the stator current history. The performance of the developed fault analysis method is investigated using Matlab/Simulink® software. Stator turns faults are detected through current monitoring of a 2 Hp three phase induction motor under various loading conditions. Fault history is calculated under various loading conditions, and a wide range of fault severity.

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32

DIGĂ, Nicolae, Valentin NĂVRĂPESCU, Silvia-Maria DIGĂ, Adelaida-Mihaela DUINEA, and Gabriel VOCHESCU. "Modern aspects of calculation and analysis of the operating regimes of centrifugal pumps driven by induction motors, within the ancillary services of thermoelectric power plants." EMERG - Energy. Environment. Efficiency. Resources. Globalization 6, no. 3 (2020): 54–65. http://dx.doi.org/10.37410/emerg.2020.3.05.

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In this paper, the authors present a systematized methodology for modelling and analyzing the operating regimes of centrifugal pumps as working machines in electric drive systems. For solving, algorithms and calculation programs developed in the Mathcad programming environment were designed. For example, a representative case study was chosen of a condensing electric pump from the own services of a thermoelectric power plant with groups of 500 MW, driven by an induction motor with a squirrel cage rotor of 6 kV. It was thus possible to comparatively analyze two solutions for regulating the flow of a centrifugal pump in terms of energy efficiency.

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33

Kouki, Hajer, Mouldi Ben Fredj, and Habib Rehaoulia. "Double star induction machine modelling: Impact of the stator mutual leakage inductance." International Journal of Applied Electromagnetics and Mechanics 53, no. 1 (January 10, 2017): 51–61. http://dx.doi.org/10.3233/jae-150160.

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34

Gholami, Mehrdad, Om‐Kolsoom Shahryari, and Hadi Tarimoradi. "An extended winding function model for induction machine modelling considering saturation effect." IET Electric Power Applications 15, no. 1 (December 13, 2020): 79–91. http://dx.doi.org/10.1049/elp2.12006.

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35

Ai, Yongle, Yumei Wang, and Kamper Marrten. "Modelling and control of six-phase induction machine under special current waveform." International Journal of Modelling, Identification and Control 10, no. 1/2 (2010): 4. http://dx.doi.org/10.1504/ijmic.2010.033838.

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36

Titova, T. S., A. M. Evstaf’ev, and A. A. Pugachev. "Improving the energy efficiency of electric drives for auxiliary units of traction rolling stock." Journal of Physics: Conference Series 2131, no. 4 (December 1, 2021): 042085. http://dx.doi.org/10.1088/1742-6596/2131/4/042085.

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Abstract The review of technical solutions and schematic characteristics of auxiliary drives for traction vehicles has shown that the most rational variant is an electric drive with an induction machine. Given the operating modes of the auxiliary drives and the share of their power consumption in the total locomotive power, the task of using scalar control systems for induction machines becomes relevant. Based on a mathematical model describing the dynamic energy conversion processes in the T-shape substitution circuit of an induction motor, taking into account stator steel losses and current displacement effects in the rotor winding and saturation along the main magnetic path, possibilities for reducing stator current have been investigated. In order to improve the energy efficiency of electric drives two variants of control system have been proposed. One based on search method of self-tuning to the stator current minimum and the other - on maintaining the power factor of induction motor at the level that ensures equality of active and reactive components of stator current. The hardware and software requirements for implementing control systems have been analysed. Modelling using Matlab has shown that both control systems work - power loss reduction can be as low as 50% and as high as 60% in certain modes.

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37

Levi, E., and Z. Krzeminski. "Main flux-saturation modelling in d-q axis models of induction machines using mixed current-flux state-space models." European Transactions on Electrical Power 6, no. 3 (September 7, 2007): 207–15. http://dx.doi.org/10.1002/etep.4450060311.

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38

Ouadi, H., F. Giri, A. Elfadili, Ph Dorleans, and J. F. Massieu. "Induction Machine Control in Presence of Magnetic hysteresis Modelling and Speed reference tracking." IFAC Proceedings Volumes 43, no. 10 (2010): 7–12. http://dx.doi.org/10.3182/20100826-3-tr-4015.00005.

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39

Bottauscio, O., M. Chiampi, C. Concari, C. Tassoni, and M. Zucca. "From the ideal to the real induction machine: Modelling approach and experimental validation." Journal of Magnetism and Magnetic Materials 320, no. 20 (October 2008): e901-e906. http://dx.doi.org/10.1016/j.jmmm.2008.04.049.

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40

Riu, Delphine, Nicolas Retière, and Marcel Ivanès. "Diffusion phenomenon modelling by half-order systems: application to squirrel-cage induction machine." Journal of Magnetism and Magnetic Materials 242-245 (April 2002): 1243–45. http://dx.doi.org/10.1016/s0304-8853(01)01198-2.

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41

Ogunjuyigbe, A. S. O., T. R. Ayodele, and B. B. Adetokun. "Modelling and analysis of dual stator-winding induction machine using complex vector approach." Engineering Science and Technology, an International Journal 21, no. 3 (June 2018): 351–63. http://dx.doi.org/10.1016/j.jestch.2018.03.013.

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42

Mesai-ahmed, Hamza, Abderrahim Bentaallah, Antonio J. Marques Cardoso, Youcef Djeriri, and Imed Jlassi. "Robust Neural Control of the Dual Star Induction Generator Used in a Grid-Connected Wind Energy Conversion System." Mathematical Modelling of Engineering Problems 8, no. 3 (June 24, 2021): 323–32. http://dx.doi.org/10.18280/mmep.080301.

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This paper presents a field-oriented control (FOC) of a dual star induction generator (DSIG) applied in a grid-connected wind energy conversion system. Currently, the dual star induction machine (DSIM) is increasingly used among multiphase machines. The machine has two star-connections, sharing the same stator offset, by an electrical angle of 30° and fed by two parallel converters. Maximum power point tracking (MPPT) is illustrated in a first stage, in order to extract a maximum of power under fluctuating wind speed. In a second stage, vector control of a DSIG with FOC is described. Finally, voltage oriented control (VOC) is used to ensure the power factor unity on the grid side. The main contribution of the presented paper is the application of a simple architecture of an artificial neural network (ANN) controller in order to improve the robustness and stability of the system, especially against the parameter change. In comparison with the conventional control, which is known by its sensitivity, the proposed neural MPPT with neural FOC (NMPPT-NFOC) presents better performance under normal and abnormal conditions. The robustness and effectiveness of the proposed control has been validated through illustrative simulation results with different functional zones, and for fixed and variable wind speed.

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Ahsan, Hailiya, and Mairaj-ud-Din Mufti. "Modelling and stability investigations of an aggregate wind farm–fed multi-machine system." Wind Engineering 44, no. 6 (July 15, 2019): 596–609. http://dx.doi.org/10.1177/0309524x19862759.

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This article presents a detailed mathematical modelling and integration of a substantial 300-MW wind farm in a New England 39-bus system for stability investigations. Machine modelling is achieved using the differential algebraic equations from the two-axis model, in the form of a flexible network function. An aggregated wind farm model is developed with the order of hundreds of wind turbines, driving an aggregate doubly fed induction machine feeding the multi-machine system. Stability studies are performed on the non-linear model in MATLAB-Simulink platform, with exogenous disturbances of a continuous disturbed wind and a three-phase short circuit with two different clearing times. Stability retention of the wind farm–fed system is affirmed with the extensive power balance, frequency supervision and profuse voltage levelling.

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Guellout, O., A. Rezig, S. Touati, and A. Djerdir. "Elimination of broken rotor bars false indications in induction machines." Mathematics and Computers in Simulation 167 (January 2020): 250–66. http://dx.doi.org/10.1016/j.matcom.2019.06.010.

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Cortés, Camilo Andrés, Wim Deprez, Johan Driesen, and Jhon J. Pérez. "Determining electrical loss in electromagnetically-modelled induction motors using the finite element method." Ingeniería e Investigación 28, no. 3 (September 1, 2008): 64–74. http://dx.doi.org/10.15446/ing.investig.v28n3.15122.

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This paper shows the pattern of a 7.5 kW squirrel-cage induction motor’s electrical loss in balanced and unbalanced conditions, modelling the motor using the finite element method and comparing the results with experimental data obtained in the laboratory for the selected motor. Magnetic flux density variation was analysed at four places in the machine. The results so obtained showed that the undervoltage unbalanced condition was the most critical from the motor’s total loss point of view. Regarding variation of loss in parts of the motor, a constant iron loss pattern was found when the load was changed for each type of voltage supply and that the place where the loss had the largest rise was in the machine’s rotor.

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Devanneaux, V., B. Dagues, J. Faucher, and G. Barakat. "An accurate model of squirrel cage induction machines under stator faults." Mathematics and Computers in Simulation 63, no. 3-5 (November 2003): 377–91. http://dx.doi.org/10.1016/s0378-4754(03)00083-1.

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Ghani, Sayeed Nurul. "On simulating dynamic behaviour of three phase induction machines with squirrel cage rotor." SIMULATION 50, no. 5 (May 1988): 182–93. http://dx.doi.org/10.1177/003754978805000503.

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Martinez-Roman, Javier, Ruben Puche-Panadero, Angel Sapena-Bano, Carla Terron-Santiago, Jordi Burriel-Valencia, and Manuel Pineda-Sanchez. "Analytical Model of Induction Machines with Multiple Cage Faults Using the Winding Tensor Approach." Sensors 21, no. 15 (July 27, 2021): 5076. http://dx.doi.org/10.3390/s21155076.

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Induction machines (IMs) are one of the main sources of mechanical power in many industrial processes, especially squirrel cage IMs (SCIMs), due to their robustness and reliability. Their sudden stoppage due to undetected faults may cause costly production breakdowns. One of the most frequent types of faults are cage faults (bar and end ring segment breakages), especially in motors that directly drive high-inertia loads (such as fans), in motors with frequent starts and stops, and in case of poorly manufactured cage windings. A continuous monitoring of IMs is needed to reduce this risk, integrated in plant-wide condition based maintenance (CBM) systems. Diverse diagnostic techniques have been proposed in the technical literature, either data-based, detecting fault-characteristic perturbations in the data collected from the IM, and model-based, observing the differences between the data collected from the actual IM and from its digital twin model. In both cases, fast and accurate IM models are needed to develop and optimize the fault diagnosis techniques. On the one hand, the finite elements approach can provide highly accurate models, but its computational cost and processing requirements are very high to be used in on-line fault diagnostic systems. On the other hand, analytical models can be much faster, but they can be very complex in case of highly asymmetrical machines, such as IMs with multiple cage faults. In this work, a new method is proposed for the analytical modelling of IMs with asymmetrical cage windings using a tensor based approach, which greatly reduces this complexity by applying routine tensor algebra to obtain the parameters of the faulty IM model from the healthy one. This winding tensor approach is explained theoretically and validated with the diagnosis of a commercial IM with multiple cage faults.

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Bialobrzheskyi, O., V. Nozhenko, and O. Todorov. "Influence of misalignment of connection of electrical machine shafts on the nature of electric power of the induction motor." Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, no. 6 (December 25, 2022): 90–96. http://dx.doi.org/10.33271/nvngu/2022-6/090.

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Purpose. To identify the vibration power components caused by misalignment of electrical machine shafts in the instantaneous power of the induction motor. Methodology. The power components of the induction motor are analytically determined taking into account the power caused by torque vibrations on the shaft. Based on this, using the methods of mathematical modelling in the visual programming environment, the known model of a three-phase induction motor with a short-circuited rotor has been made. In addition, elements and connections are introduced which realize the formation of the moment caused by the imbalance of rotating masses. Using Fourier transform of the electric power of the induction motor, we determine its discrete spectrum. Experimental research is conducted on the electric power of the induction motor with a short-circuited rotor, in similar model conditions, on laboratory equipment. With the use of a virtual device synthesized in the LabVIEW package, the wavelet analysis of stator electric power of the motor of laboratory electrotechnical complex is performed. Findings. Differential equations of the induction motor with a short-circuited rotor in abc coordinate system are obtained, which reflect the distribution of instantaneous power in the machine taking into account the vibration moment. As a result of modelling according to the specified equations of the induction machine, in the conditions of full symmetry of parameters of the scheme and the mode with eccentricity of rotating masses, low-frequency vibrations of electric power of a stator with frequency of 25 Hz have been found. Similar results were obtained as a result of wavelet analysis of the electric power of an induction motor of a laboratory electrotechnical complex. Originality. Rationality of use of instantaneous electrical power of induction motor stator for detection of vibration caused by misalignment between its shaft and the shaft of another machine has been substantiated, which allows detecting vibration without complex methods of measuring vibration displacement and its derivatives. Practical value. Detecting vibration by measuring the electrical parameters of the stator circuit of the induction motor and determining the vibrations of its instantaneous power without the use of specialized equipment significantly simplify the procedure of vibration diagnostics at its early stages.

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Ratni, Azeddine, and Djamel Benazouz. "Mathematical modelling of rolling element bearings fault for the diagnosis in the gearbox-induction machine." Mathematical Models in Engineering 6, no. 1 (March 31, 2020): 1–12. http://dx.doi.org/10.21595/mme.2020.21206.

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