Please use this identifier to cite or link to this item:
Title: Review of soft computing models in design and control of rotating electrical machines
Authors: Dineva, A
Mosavi, A
Ardabili, S
Vajda, I
Shamshirband, S
Rabczuk, T
Chau, KW 
Keywords: Artificial intelligence
Big data
Computational intelligence
Data science
Deep learning
Electric motor drives
Electric vehicles
Electrical engineering
Energy informatics
Energy management
Energy systems
Ensemble models
Hybrid models
Machine learning
Rotating electrical machines
Soft computing
Issue Date: 2019
Publisher: Molecular Diversity Preservation International (MDPI)
Source: Energies, 2019, v. 12, no. 6, 1049 How to cite?
Journal: Energies 
Abstract: Rotating electrical machines are electromechanical energy converters with a fundamental impact on the production and conversion of energy. Novelty and advancement in the control and high-performance design of these machines are of interest in energy management. Soft computing methods are known as the essential tools that significantly improve the performance of rotating electrical machines in both aspects of control and design. From this perspective, a wide range of energy conversion systems such as generators, high-performance electric engines, and electric vehicles, are highly reliant on the advancement of soft computing techniques used in rotating electrical machines. This article presents the-state-of-the-art of soft computing techniques and their applications, which have greatly influenced the progression of this significant realm of energy. Through a novel taxonomy of systems and applications, the most critical advancements in the field are reviewed for providing an insight into the future of control and design of rotating electrical machines.
EISSN: 1996-1073
DOI: 10.3390/en12061049
Rights: © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (
The following publication Dineva A, Mosavi A, Faizollahzadeh Ardabili S, Vajda I, Shamshirband S, Rabczuk T, Chau K-W. Review of Soft Computing Models in Design and Control of Rotating Electrical Machines. Energies. 2019; 12(6):1049 is available at
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
Dineva_Review_soft_computing.pdf2.52 MBAdobe PDFView/Open
View full-text via PolyU eLinks SFX Query
Show full item record
PIRA download icon_1.1View/Download Contents


Citations as of Nov 30, 2019


Citations as of Dec 5, 2019

Page view(s)

Citations as of Dec 4, 2019


Citations as of Dec 4, 2019

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.