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 language | English |
|---|---|
| Article number | 1049 |
| Journal | Energies |
| Volume | 12 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 18 Mar 2019 |
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
