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Machines
Special Issues
Design and Control of Rotating Electrical Machines
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Design and Control of Rotating Electrical Machines

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Machines Testing and Maintenance".

Deadline for manuscript submissions: closed (15 December 2020) | Viewed by 6181

Special Issue Editor

Prof. Dr. Istvan Vajda

E-Mail Website1 Website2
Guest Editor
Institute of Automation, Kando Kalman Faculty of Electrical Engineering, Obuda University, 1034 Budapest, Hungary
Interests: soft computing; artificial intelligence; machine learning; rotating electrical machines; energy systems; deep learning; electric vehicles; big data; hybrid models; ensemble models; energy informatics; electrical engineering; computational intelligence; data science; energy management; control; electric motor drives

Special Issue Information

Dear Colleagues,

What makes the science of electrical machinery fresh, contemporary, and progressive? Materials: new conducting materials up to superconducting, new isolation materials, new structural materials, new sheet materials, new permanent magnet materials, and relevant changes in design and operations resulting in sufficiently better machine performance. Rapid progress of power electronics makes electrical drives much quicker, more efficient, and more flexible. Dramatic progress and penetration of informatics, including artificial intelligence, promote intelligent machines and drives. Rapid advances in computer techniques allow forr the use of sophisticated FEM software up to 3D, coupled fields, and multidisciplinary optimization techniques. New, emerging applications pose new needs and requirements, resulting in new solutions for design and diagnosis. All this is the frame of the Special Issue. We are looking forward to receiving articles on the above tendencies that foster the progress of electrical machines and applications.

  • Drivetrains for electrical vehicles;
  • Design of rotating machines;
  • Diagnosis of electrical machines and drives;
  • Control of electrical drives;
  • Application of space phasor to operation and diagnosis;
  • Application of new materials;
  • Multidisciplinary design optimization of electrical machines and applications;
  • Conceptual design of new types of electrical machines.

Prof. Dr. Istvan Vajda
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Machines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

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20 pages, 5518 KiB  
Article
Advanced Strategy of Speed Predictive Control for Nonlinear Synchronous Reluctance Motors
by Ahmed Farhan, Mohamed Abdelrahem, Christoph M. Hackl, Ralph Kennel, Adel Shaltout and Amr Saleh
Machines 2020, 8(3), 44; https://doi.org/10.3390/machines8030044 - 1 Aug 2020
Cited by 20 | Viewed by 3586
Abstract
To gain fast dynamic response, high performance, and good tracking capability, several control strategies have been applied to synchronous reluctance motors (SynRMs). In this paper, a nonlinear advanced strategy of speed predictive control (SPC) based on the finite control set model predictive control [...] Read more.
To gain fast dynamic response, high performance, and good tracking capability, several control strategies have been applied to synchronous reluctance motors (SynRMs). In this paper, a nonlinear advanced strategy of speed predictive control (SPC) based on the finite control set model predictive control (FCS-MPC) is proposed and simulated for nonlinear SynRMs. The SPC overcomes the limitation of the cascaded control structure of the common vector control by employing a novel strategy that considers all the electrical and mechanical variables in one control law through a new cost function to obtain the switching signals for the power converter. The SynRM flux maps are known based on finite element method (FEM) analysis to take into consideration the effect of the nonlinearity of the machine. To clear the proposed strategy features, a functional and qualitative comparison between the proposed SPC, field-oriented control (FOC) with an anti-windup scheme, and current predictive control (CPC) with outer PI speed control loop is presented. For simplicity, particle swarm optimization (PSO) is performed to tune all the unknown parameters of the control strategies. The comparison features include controller design, dynamic and steady-state behaviors. Simulation results are presented to investigate the benefits and limitations of the three control strategies. Finally, the proposed SPC, FOC, and CPC have their own merits, and all methods encounter the requirements of advanced high-performance drives. Full article
(This article belongs to the Special Issue Design and Control of Rotating Electrical Machines)
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11 pages, 1126 KiB  
Letter
Limited-Position Set Model-Reference Adaptive Observer for Control of DFIGs without Mechanical Sensors
by Mohamed Abdelrahem, Christoph M. Hackl and Ralph Kennel
Machines 2020, 8(4), 72; https://doi.org/10.3390/machines8040072 - 12 Nov 2020
Cited by 13 | Viewed by 2001
Abstract
Operations of the doubly-fed induction generators (DFIGs) without mechanical sensors are highly desirable in order to enhance the reliability of the wind generation systems. This article proposes a limited-position set model-reference adaptive observer (LPS-MRAO) for control of DFIGs in wind turbine systems (WTSs) [...] Read more.
Operations of the doubly-fed induction generators (DFIGs) without mechanical sensors are highly desirable in order to enhance the reliability of the wind generation systems. This article proposes a limited-position set model-reference adaptive observer (LPS-MRAO) for control of DFIGs in wind turbine systems (WTSs) without mechanical sensors, i.e., without incremental encoders or speed transducers. The concept of of the developed LPS-MRAO is obtained from the finite-set model predictive control (FS-MPC). In the proposed LPS-MRAO, an algorithm is presented in order to give a constant number of angles for the rotor position of the DFIG. By using these angles, a certain number of rotor currents can be predicted. Then, a new quality function is defined to find the best angle of the rotor. In the proposed LPS-MRAO, there are not any gains to tune like the classical MRAO, where a proportional-integral is used and must be tuned. Finally, the proposed LPS-MRAO and classical one are experimentally implemented in the laboratory and compared at various operation scenarios and under mismatches in the parameters of the DFIG. The experimental results illustrated that the estimation performance and robustness of the proposed LPS-MRAO are better than those of the classical one. Full article
(This article belongs to the Special Issue Design and Control of Rotating Electrical Machines)
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