Condition Monitoring, Reliability Analysis, and Fault Detection of Power Electronics
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F3: Power Electronics".
Deadline for manuscript submissions: 20 July 2026 | Viewed by 771
Editors
Interests: fault diagnosis; reinforcement learning; unsupervised learning
Special Issues, Collections and Topics in MDPI journals
Interests: health monitoring; intelligent identification; transfer learning; deep learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid development of power electronics has enabled high-efficiency energy conversion in renewable energy systems, electric vehicles, aerospace power supplies, smart grids and industrial automation. However, the increasing integration level, higher power density and harsh operating environments have significantly aggravated reliability challenges in power electronic systems. Failures of key components not only lead to system downtime but may also cause severe safety and economic consequences. Therefore, advanced condition monitoring, reliability analysis and fault detection techniques have become essential for ensuring the safe, stable and long-term operation of power electronic equipment.
This Special Issue aims to provide a comprehensive forum for recent advances in condition monitoring, fault diagnosis, prognostics and the reliability-oriented design of power electronics. Emphasis is placed on both theoretical developments and practical applications, covering data-driven, model-based and hybrid approaches. With the increasing availability of high-frequency sensing data and the rapid progress of artificial intelligence, machine learning and digital twin technologies, new opportunities have emerged for early fault detection, degradation assessment and the remaining useful life (RUL) prediction of power electronic components and systems.
Topics of interest include, but are not limited to, health monitoring and fault diagnosis of power semiconductor devices, capacitors and passive components, reliability modeling under multi-physics stresses and online condition monitoring methods using electrical, thermal, acoustic or vibration signals. Contributions addressing advanced signal processing, deep learning, reinforcement learning and uncertainty-aware reliability analysis are particularly encouraged. In addition, system-level fault-tolerant control strategies, reliability evaluation for wide-bandgap devices and condition-based maintenance frameworks are also within the scope of this Special Issue.
By bringing together researchers and practitioners from academia and industry, this Special Issue aims to promote cross-disciplinary collaboration and provide state-of-the-art insights into enhancing the reliability, safety and intelligence of modern power electronic systems.
Dr. Ruixin Wang
Dr. Zhenghong Wu
Guest Editors
Manuscript Submission Information
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Keywords
- power electronics
- condition monitoring
- fault detection and diagnosis
- reliability analysis
- prognostics and health management (PHM)
- remaining useful life (RUL) prediction
- power semiconductor devices
- wide-bandgap devices
- data-driven and AI-based methods
- fault-tolerant control
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