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Special Issue "Selected Papers from IEEE ICKII 2018..."

A special issue of Energies (ISSN 1996-1073).

Deadline for manuscript submissions: 31 December 2018

Special Issue Editors

Guest Editor
Prof. Dr. Teen-Hang Meen

Distinguished Professor, Department of Electronic Engineering, National Formosa University, Yunlin 632, Taiwan
Website | E-Mail
Interests: photovoltaic device; dye-sensitized solar cells; nanotechnology
Guest Editor
Prof. Dr. Wenbing Zhao

Department of Electrical Engineering and Computer Science, College of Engineering, Cleveland State University, Cleveland, OH 44115, USA
Website | E-Mail
Interests: smart healthcare; motion tracking; computer vision; human–computer interaction; distributed systems

Special Issue Information

Dear Colleagues,

The 1st IEEE International Conference on Knowledge Innovation and Invention 2018 (IEEE ICKII 2018) will be held on Jeju Island, South Korea, 23–27 July, 2018, and it will provide a unified communication platform for researchers on the topics of information technology, innovation design, communication science and engineering, industrial design, creative design, applied mathematics, computer science, electrical and electronic engineering, mechanical and automation engineering, green technology and architecture engineering, material science and other related fields. This Special Issue on “Selected Papers from IEEE ICKII 2018” is expected to select excellent papers presented at IEEE ICKII 2018 on the topic of energies. This Special Issue provides related scientific research, technology development and policy and management studies. It publishes reviews and regular research papers. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. Full experimental details must be provided so that the results can be reproduced. We invite investigators to contribute original research articles, as well as review articles, to this Special Issue. Potential topics include, but are not limited to:

  • Energy Fundamentals
  • Primary Energy Sources
  • Secondary Energy Sources and Energy Carriers
  • Energy Exploration
  • Intermediate and Final Energy Use
  • Energy Conversion Systems
  • Energy Policy
  • Exergy
  • Energetics
  • Energy Research and Development

Prof. Dr. Teen­-Hang Meen
Prof. Dr. Wenbing Zhao
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 papers will be 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. Energies 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 1600 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.

Published Papers (1 paper)

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Research

Open AccessArticle Online Speed Estimation Using Artificial Neural Network for Speed Sensorless Direct Torque Control of Induction Motor based on Constant V/F Control Technique
Energies 2018, 11(8), 2176; https://doi.org/10.3390/en11082176
Received: 9 August 2018 / Revised: 15 August 2018 / Accepted: 19 August 2018 / Published: 20 August 2018
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Abstract
This paper presents the speed estimator for speed sensorless direct torque control of a three-phase induction motor based on constant voltage per frequency (V/F) control technique, using artificial neural network (ANN). The estimated stator current equation is derived and rearranged consistent with the
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This paper presents the speed estimator for speed sensorless direct torque control of a three-phase induction motor based on constant voltage per frequency (V/F) control technique, using artificial neural network (ANN). The estimated stator current equation is derived and rearranged consistent with the control algorithm and ANN structure. For the speed estimation, a weight in ANN, which relates to the speed, is adjusted by using Widrow–Hoff learning rule to minimize the sum of squared errors between the measured stator current and the estimated stator current from ANN output. The consequence of using this method leads to the ability of online speed estimation and simple ANN structure. The simulation and experimental results in high- and low-speed regions have confirmed the validity of the proposed speed estimation method. Full article
(This article belongs to the Special Issue Selected Papers from IEEE ICKII 2018...)
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