Finite-Element and Analytical Calculations of No-Load Core Losses in Energy-Saving Induction Motors

Komęza, Krzysztof; Dems, M.

doi:10.1109/tie.2011.2168795

Cited by 63 publications

(30 citation statements)

References 29 publications

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“…the machine's magnetic field is first calculated and then decomposed in its harmonic content to better understand the results of the calculation, e.g. [17], [18]. Evidently, these articles give only little insight in the harmonic content of electric machines in general, let alone the physical cause for those harmonics.…”

Section: A Literaturementioning

confidence: 99%

“…This implies that all the harmonic combinations that satisfy either (17) or (18) will be present in the magnetic field. The above is summarized in Table I.…”

Section: Load Conditionsmentioning

confidence: 99%

“…It is shown that applying the above theory results in a huge reduction of the FB model's computational time. The first example evaluates the effect of an increasing number of slots per pole and per phase on the harmonic content of the no-load field using (17). If q is increased, the number of slots (N s = 2mpq) increases as well.…”

Section: Examplesmentioning

confidence: 99%

“…If q is increased, the number of slots (N s = 2mpq) increases as well. According to (17) this implies fewer spatial-harmonic content. This was indeed expected, increasing the number of slots per pole and per phase is a well-known technique to reduce the harmonic content.…”

Section: Examplesmentioning

confidence: 99%

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Time- and Spatial-Harmonic Content in Synchronous Electrical Machines

2016

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The use of power electronics has led to a growing importance of higher time-harmonic content in electrical machines. To gain insight in phenomena related to these higher harmonics, such as noise and losses, a good understanding of the magnetic field's harmonic content is mandatory. Moreover, the development of fast and accurate, harmonic-based, analytical models requires a qualitative knowledge of the machine's time-and spatial-harmonic content. Although the harmonic content of electric machines is an extensively studied topic, previous publications tended to focus on one type of synchronous machines and often didn't consider higher time-harmonic orders. This work complements the existing theory by providing a more general approach, thereby covering machines and operating points that weren't covered until now. It considers both three-phase and multi-phase machines with an odd number of phases. The winding distribution can either have an integer or a fractional number of slots per pole and per phase and higher time-harmonic content is regarded as well. Note that saturation is neglected. Despite its general validity, the work succeeds at providing one simple equation to determine the machine's time-and spatial-harmonic content. Moreover, the work also extensively discusses the physical causes of the harmonic content. The combination of this general validity, the simple result and the insight in the physics makes that this work is a strong tool to both study harmonic-related phenomena in electric machines and to develop harmonic-based analytical models.

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Section: A Literaturementioning

confidence: 99%

“…This implies that all the harmonic combinations that satisfy either (17) or (18) will be present in the magnetic field. The above is summarized in Table I.…”

Section: Load Conditionsmentioning

confidence: 99%

Section: Examplesmentioning

confidence: 99%

Section: Examplesmentioning

confidence: 99%

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Time- and Spatial-Harmonic Content in Synchronous Electrical Machines

2016

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“…nergy efficiency of continuous-duty (S1) motors [1], such applications as pumps, blowers, and fans is a subject of increasing interest [2]− [4]. However, intermittent duty (S3) motors have not been studied to that extent.…”

Section: Introductionmentioning

confidence: 99%

Energy efficiency of hoisting motors

Repo¹,

Montonen

Sizonenko

et al. 2014

2014 International Conference on Electrical Machines (ICEM)

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Since 2009 she has been with Konecranes, Finland. Her research interests include electrical machines and drives, energy-efficiency design, and hybridization. Juho Montonen was born in 1988 in Joutseno, Finland. He received the Master of Science (M.Sc.) degree from Lappeenranta University of Technology (LUT), Finland in 2012 and Bachelor of Science (B.Sc.) in 2011. He is currently doctoral student in LUT. He is doing the research concerning about electrical machines and drives. His research work focuses on permanent magnet motors, especially those which are used in different kinds of traction applications. Vitaliy Sizonenko was born in 1989 in Tomilino, Russia, received the Master of Science (M.Sc.) degree from Moscow Power Engineering Institute (MPEI), Russia and from Lappeenranta University of Technology (LUT), Finland in 2012 (double degree programme), the Bachelor of Science (B.Sc.) degree from MPEI in 2010. Pia Lindh received the D.Sc. (Tech.) degree in 2004 from Lappeenranta University of Technology. She currently works as a researcher teacher at the Department of Electrical Engineering. Her research interests include a wide range of electrical machines and drives, permanent-magnet machines and traction applications in particular. Juha Pyrhönen, a Member of IEEE, was born in 1957 in Kuusankoski, Finland, received the Doctor of Science (D.Sc.) degree from Lappeenranta University of Technology (LUT), Finland in 1991. He became an Associate Professor of Electrical Engineering at LUT in 1993 and a Professor of Electrical Machines and Drives in 1997. He is currently the Head of the Department of Electrical Engineering, where he is engaged in research and development of electric motors and electric drives.His current interests include different synchronous machines and drives, induction motors and drives and solid-rotor high-speed induction machines and drives.

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Real‐time condition monitoring on VSD‐fed induction motors through statistical analysis and synchronous speed observation

Cabal-Yépez

Fernandez‐Jaramillo

García-Pérez

et al. 2014

Int. Trans. Electr. Energ. Syst.

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SUMMARYInduction motors are key elements of every industrial process. A faulty motor produces interruptions on production lines, with consequences in cost, product quality, and safety. The relevance in induction motor monitoring is the ability to detect faults in incipient state. Many proposed methods consider direct connection of motors to the power supply; however, the common practice in industry is to connect them through variable speed drives (VSD), which introduce harmonics into the current supply signal that make the fault identification extremely difficult. This work proposes a statistical analysis through mean, variance, and information entropy computation, combined with sensorless rotating speed estimation for classifying different faults in induction motors using an artificial neural network. The proposed methodology examines the voltage and current signals provided by an industrial VSD that ensures a high certainty on identifying the treated faults at different rotational speed. A field programmable gate array-based implementation is developed to offer an online, system-on-chip solution for real-time condition monitoring.

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Finite-Element and Analytical Calculations of No-Load Core Losses in Energy-Saving Induction Motors

Cited by 63 publications

References 29 publications

Time- and Spatial-Harmonic Content in Synchronous Electrical Machines

Time- and Spatial-Harmonic Content in Synchronous Electrical Machines

Energy efficiency of hoisting motors

Real‐time condition monitoring on VSD‐fed induction motors through statistical analysis and synchronous speed observation

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