Data-Driven Methods for Design and Analysis of Electromagnetic Devices: 2nd Edition
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".
Deadline for manuscript submissions: 20 July 2025 | Viewed by 8808
Special Issue Editors
Interests: computational electromagnetics; advanced electrical machines and drive systems for electric vehicles; optimal energy management systems for microgrids and virtual power plants; multidisciplinary design optimization methods based on AI and cloud services
Special Issues, Collections and Topics in MDPI journals
Interests: advanced electrical machine design and optimization; measurement and modeling of magnetic properties of magnetic materials; multi-disciplinary analysis and system-level robust optimisation of electromagnetic devices; electric motor drives and control
Special Issues, Collections and Topics in MDPI journals
Interests: electromagnetic and coupled multi-physical field analysis; measurement and modeling of magnetic properties of materials; optimum design of electromagnetic devices and systems; novel electrical machines and drive systems, power systems, and renewable energy technologies
Special Issues, Collections and Topics in MDPI journals
Interests: electromagnetic field; numerical analysis; multi-physics coupling and its application in engineering
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Electromagnetic devices have been widely employed in domestic appliances and industrial equipment, for example, as electrical drive systems for electrical vehicles. In the context of Industry 4.0, their analysis methods are experiencing significant progress and innovation due to the integration of industrial big data. To facilitate this progress, data-driven approaches have been investigated in the modelling, design, optimization, condition monitoring, and reliability and robustness evaluation of electromagnetic devices and systems, such as the data-driven design optimization method in permanent magnet motors in electric vehicles and data-driven fault diagnosis methods for wind power generators. These new models and analysis methods will benefit the development of digital twin for electromagnetic devices.
This Special Issue aims to present a collection of scientific manuscripts covering the theoretical and practical aspects associated with data-driven methods for the design and analysis of electromagnetic devices and systems. State-of-the-art and emerging developments in this field are welcome. Topics may include, but are not limited to, the following:
- Model-based analysis and design optimization of electromagnetic devices;
- Data-driven modelling of electromagnetic devices;
- Data-driven design optimization of electromagnetic devices;
- Data-driven methods for the devices’ control systems;
- Data-driven condition monitoring methods for electromagnetic devices;
- Evaluation of reliability and robustness;
- Hybrid data-driven and model-based methods.
Dr. Gang Lei
Prof. Dr. Youguang Guo
Prof. Dr. Jianguo Zhu
Prof. Dr. Yujiao Zhang
Guest Editors
Dr. Bo Ma
Guest Editor Assistant
Manuscript Submission Information
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Keywords
- model-based analysis and design optimization of electromagnetic devices
- data-driven modelling of electromagnetic devices
- data-driven design optimization of electromagnetic devices
- data-driven methods for the devices’ control systems
- data-driven condition monitoring methods for electromagnetic devices
- evaluation of reliability and robustness
- hybrid data-driven and model-based methods
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