Review of soft computing models in design and control of rotating electrical machines

Adrienn Dineva, Amir Mosavi, Sina Faizollahzadeh Ardabili, I. Vajda, Shahaboddin Shamshirband, Timon Rabczuk, Kwok Wing Chau

Research output: Contribution to journalReview article

3 Citations (Scopus)

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.

Original languageEnglish
Article number1049
JournalEnergies
Volume12
Issue number6
DOIs
Publication statusPublished - Mar 18 2019

Fingerprint

Electrical Machines
Soft computing
Soft Computing
Rotating
Energy
High Performance
Energy management
Taxonomies
Electric vehicles
Energy conversion
Computing Methods
Energy Management
Electric Vehicle
Taxonomy
Progression
Converter
Model
Engines
Engine
Generator

Keywords

  • Artificial intelligence
  • Big data
  • Computational intelligence
  • Control
  • 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

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Energy Engineering and Power Technology
  • Energy (miscellaneous)
  • Control and Optimization
  • Electrical and Electronic Engineering

Cite this

Dineva, A., Mosavi, A., Ardabili, S. F., Vajda, I., Shamshirband, S., Rabczuk, T., & Chau, K. W. (2019). Review of soft computing models in design and control of rotating electrical machines. Energies, 12(6), [1049]. https://doi.org/10.3390/en12061049

Review of soft computing models in design and control of rotating electrical machines. / Dineva, Adrienn; Mosavi, Amir; Ardabili, Sina Faizollahzadeh; Vajda, I.; Shamshirband, Shahaboddin; Rabczuk, Timon; Chau, Kwok Wing.

In: Energies, Vol. 12, No. 6, 1049, 18.03.2019.

Research output: Contribution to journalReview article

Dineva, A, Mosavi, A, Ardabili, SF, Vajda, I, Shamshirband, S, Rabczuk, T & Chau, KW 2019, 'Review of soft computing models in design and control of rotating electrical machines', Energies, vol. 12, no. 6, 1049. https://doi.org/10.3390/en12061049
Dineva A, Mosavi A, Ardabili SF, Vajda I, Shamshirband S, Rabczuk T et al. Review of soft computing models in design and control of rotating electrical machines. Energies. 2019 Mar 18;12(6). 1049. https://doi.org/10.3390/en12061049
Dineva, Adrienn ; Mosavi, Amir ; Ardabili, Sina Faizollahzadeh ; Vajda, I. ; Shamshirband, Shahaboddin ; Rabczuk, Timon ; Chau, Kwok Wing. / Review of soft computing models in design and control of rotating electrical machines. In: Energies. 2019 ; Vol. 12, No. 6.
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