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

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

Research output: Contribution to journalReview articlepeer-review

55 Citations (Scopus)


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
Issue number6
Publication statusPublished - 2019 Mar 18

Bibliographical note

Publisher Copyright:
© 2019 by the authors.


  • 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

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


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