| M | T | W | T | F | S | S |
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |||
| 5 | 6 | 7 | 8 | 9 | 10 | 11 |
| 12 | 13 | 14 | 15 | 16 | 17 | 18 |
| 19 | 20 | 21 | 22 | 23 | 24 | 25 |
| 26 | 27 | 28 | 29 | 30 | 31 |
With the rapid development of renewable energy, electric vehicles, and smart grids, power electronic devices—such as semiconductor devices, capacitors, and inductors—serve as core components for energy conversion and control. However, these devices have a high failure rate. Researching reliability assessment and optimization technology for power electronic devices is crucial to ensuring the safe and stable operation of power systems and promoting energy transformation. To accurately evaluate the reliability of power electronic devices, several approaches are employed, including aging acceleration testing, multi-physics modeling, failure mechanism analysis, and aging simulation. These methods help identify the root causes of faults and support the development of emerging sensing and state monitoring technologies, fault diagnosis, active thermal management, and optimized packaging design. Such advancements are essential for improving the operation and maintenance capabilities of power electronic devices. Additionally, emerging artificial intelligence and machine learning technologies are gaining significant attention for applications like aging simulation and remaining life prediction. Therefore, this topic aims to address and find solutions to the challenges associated with the reliability evaluation and optimization design of power electronic devices. Topics of interest include, but not limited to the following aspects:
1. Modeling and simulation of power electronic devices
2. Accelerated aging testing and mechanism analysis
3. Online detection and application of feature parameters
4. Proactive thermal and health management
5. Life modeling and state assessment techniques
6. Emerging sensing and integration technologies
7. Packaging improvements for reliability optimization
8. Data-driven techniques for reliability quantification
Prof. Yunze He, Hunan University, China
Associate Prof. Wei Lai, Chongqing University, China
Associate Prof. Jun Zhang, Hohai University, China
Associate Prof. Zhaoyang Zhao, Southwest Jiaotong University, China
Post-doctoral Ran Yao, Chongqing University, China
1. All papers will undergo a thorough peer review process. Accepted full papers that are presented at the conference will be published in proceedings.
2. The corresponding author is responsible for ensuring that the article’s publication has been approved by all other co-authors and takes responsibility for the paper during submission and peer review.
3. Review comments will be communicated to you and you may require to do necessary revisions and send revised paper on or before prescribed day.
Reviewers evaluate article submissions to IEECSC, based on the requirements of the conference proceedings, predefined criteria, and quality, completeness and accuracy of the research presented. They suggest improvements and make a recommendation to the editor about whether to accept, reject or request changes to the article. We sincerely welcome experts in the areas of Electrical Engineering and Energy join the conference as reviewer. If you are interested in joining IEECSC as Reviewer, please click the below button to submit your information.
Apply for ReviewerThe content of any submissions should be original and must not be submitted simultaneously for consideration towards publication in any other conference or journal. Reuse of material previously published by the authors is possible under the conditions that the authors fully disclose (cite) the reference and clearly highlight the innovative contribution of the IEECSC 2025 submission and the significance of this contribution.
Copyright © 2025 IEEE International Conference on Electrical Energy Conversion Systems and Control (IEEE IEECSC 2025)