Emerging Topics in Electric Machines and Motor Drives
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".
Deadline for manuscript submissions: closed (7 November 2024) | Viewed by 314
Special Issue Editors
Interests: renewable energy; deep learning; power control; power forecasting
Special Issues, Collections and Topics in MDPI journals
Interests: deep learning; renewable energy; optimization and control science
Special Issues, Collections and Topics in MDPI journals
Interests: sustainable technologies; robotics; machine learning
Special Issue Information
Dear Colleagues,
For the Special Issue "Emerging Topics in Electric Machines and Motor Drives", the focus shifts to the transformative impact of deep learning on the advancement of electric machines and motor drives. This Special Issue will delve into how artificial intelligence, especially deep learning, is revolutionizing the design, optimization, and long-term sustainability of electric machines and motor drives. With significant advancements in data collection and processing capabilities at reduced costs, deep learning has emerged as a pivotal technology in engineering applications related to electric machines and motor drives.
Contributions to this Special Issue will encompass a broad spectrum of topics, including but not limited to the following:
- AI-driven optimization of electric machines and motor drives for improved performance and efficiency.
- Deep learning applications in the predictive maintenance and control of electric machines and motor drives.
- Innovative strategies for integrating advanced motor drives into existing power systems, robotics, and machine actuators for enhanced energy efficiency.
Additionally, the Special Issue will explore the role of AI in addressing the challenges associated with the variability and control of electric machines and motor drives, ensuring their reliability and efficiency in various applications.
This Special Issue aims to present cutting-edge research, case studies, and comprehensive reviews that explore the integration of advanced machine learning techniques with electric machines and motor drives, highlighting the potential of deep learning in transforming the future of energy technology.
Topics of Interest for Publications:
- AI-enhanced control strategies for electric machines;
- Deep learning for predictive maintenance of motor drives;
- Optimization of electric motor designs using AI;
- Integration of renewable energy sources with electric machines;
- AI in power electronics for electric machines;
- Deep learning for electric vehicle motor control;
- Machine learning for electric machine fault diagnosis;
- AI-driven energy management systems for electric machines;
- Deep learning for electric machine thermal management;
- Innovative motor drive topologies enabled by AI;
- AI in robotics: enhancing mobility and manipulation;
- Deep learning for autonomous navigation in robotics;
- Machine learning for robotic perception and sensing;
- AI-driven robotic systems for industrial automation;
- Deep learning in flexible robotics for advanced task learning and adaptation.
Dr. Majad Mansoor
Dr. Adeel Feroz Mirza
Dr. Muhammad Hamza Zafar
Guest Editors
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 submissions that pass pre-check are 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 semimonthly 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 2600 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.
Keywords
- AI-enhanced control
- deep learning
- predictive EM maintenance
- electric motor drive optimization
- renewable energy integration
- power electronics
- electric vehicle control
- fault diagnosis
- motor drive control in soft robotics
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