Publication and dissemination List

Books & Chapters

S. Zhao, F. Blaabjerg, and H. Wang, “Artificial intelligence–assisted data-driven control of power electronics systems,” in Control of Power Electronic Converters and Systems Volume 4, Academic press, 2024, pp. 219–239. doi: 10.1016/b978-0-323-85622-5.00005-5.

S. Zhao, Y. Zhang, and F. Blaabjerg, “Artificial intelligence in power electronic reliability, design, and control,” in AI for Power Electronics and Renewable Energy Systems, IET, 2024, pp. 65–82. doi: doi.org/10.1049/PBPO242E_ch3.

S. Sahoo, “Physics-informed neural network-based control of power electronic converters”, Control of power electronic converters and systems, vol. 4, pp. 309-331, 2024. doi: doi.org/10.1016/B978-0-323-85622-5.00016-X

Journal & Magazine

T. Qie, X. Zhang, C. Xiang, S. Zhao, C. Jiang, H. H. Iu, and T. Fernando. “Generative Physics Informed Machine Learning Method for DC-Link Capacitance Estimation”. IEEE Transactions on Industrial Electronics, pp. 1–11, Oct. 2024, doi: 10.1109/TIE.2024.3472313.

Y. Zhang, A. Evgrafov, S. Zhao, S. Kalker, and R. W. De Doncker, “A Sparsity-Promoting Time domain evaluation method for thermal transient measurement of power semiconductors,” IEEE Transactions on Power Electronics, pp. 1–11, Jan. 2024, doi: 10.1109/tpel.2024.3367854.

Q. Deng, S. Zhao, C. Lin, B. Gou, D. Xie, X. Ge, X. Feng, H. Wang, “A similarity-based robust Open-Circuit fault diagnosis method for dual pulse rectifiers,” IEEE Transactions on Power Electronics, pp. 1–6, Jan. 2024, doi: 10.1109/tpel.2024.3397049.

Q. Deng, X. Feng, S. Zhao, B. Gou, H. Wang, and X. Ge, “Lightweight machine learning-based diagnosis for power electronic systems subject to imbalanced data,” IEEE Journal of Emerging and Selected Topics in Industrial Electronics, pp. 1–12, Jan. 2024, doi: 10.1109/jestie.2024.3358729.

Y. Zhang, Y. Zhang and H. Wang, “gEOL: A Gradient-Based End-of-Life Criterion for Power Semiconductor Modules,” in IEEE Transactions on Power Electronics, vol. 39, no. 3, pp. 2927-2931, March 2024, doi: 10.1109/TPEL.2023.3339342.

W. Liao, Y. Zhang, D. Cao, T. Ishizaki, Z. Yang and D. Yang, “Explainable Fault Diagnosis of Oil-Immersed Transformers: A Glass-Box Model,” in IEEE Transactions on Instrumentation and Measurement, vol. 73, pp. 1-4, 2024, Art no. 2506204, doi: 10.1109/TIM.2024.3350131.

Y. Zhang, Y. Zhang, J. Zhang, F. Deng and F. Blaabjerg, “Potential Failure Risk of Fault Location for Modular Multilevel Converters Under Light Loads and a Current Reshaping-Based Solution,” in IEEE Transactions on Power Electronics, vol. 39, no. 3, pp. 3601-3612, March 2024, doi: 10.1109/TPEL.2023.3344268.

Y. Zhang , A. Evgrafov , S. Zhao . A Novel Evaluation Method of Thermal Transient Measurement by Regularization. TechRxiv. December 20, 2022.

Conferences

X. Liao, S. Chen and S. Zhao, “Gated Recurrent Units-Assisted State-Space Modeling for Electric Vehicle Temperature Prediction,” PCIM Europe 2024; International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, Nürnberg, Germany, 2024, pp. 322-329, doi: 10.30420/566262039.

M. Novak, H. Wang, and F. Blaabjerg, “Experimental Validation of Capacitor Damage Accumulation In Varying Operating Conditions”, presented at ECCE, Phoenix, AZ, USA, Oct. 20-24th, 2024.

M. Novak, I. Grobelna, U. Nyman and F. Blaabjerg, “Application of Statistical Model Checking for Robustness Comparison of Power Electronics Controllers,” 2024 IEEE 15th International Symposium on Power Electronics for Distributed Generation Systems (PEDG), Luxembourg, Luxembourg, 2024, pp. 1-6, doi: 10.1109/PEDG61800.2024.10667463.

Tutorials & Talks

Invited seminar “Digital twin and physics-informed machine learning in Power Electronics” Signify, Eindhoven, Netherlands, Jul. 2, 2024.

Invited talk “Remaining Useful Life Prediction in Condition & Health Monitoring: Case Studies and Challenges” ECPE workshop on condition and health monitoring, Bilbao, Spain, Jun. 28, 2024.

Invited seminar “Synergizing Knowledge and Data for AI-assisted Condition and Health monitoring in Power Electronics” IEEE Power Electronics Society, Mar. 6, 2024.

D3A 2.0 (Danish Digitalization, Data Science and AI): Resource-Aware Machine Learning

S. Sahoo, and M. Novak, “Carbon cost of AI – impact on the maritime sector”, presented at Digital Tech Summit 2024, Copenhagen, DK, 30-31st Oct.,2024

S. Busquets-Monge, A. Sangwongwanich, and M. Novak, “Three-Level Neutral-Point-Clamped Converters: When Two Levels are not Enough”, presented at APEC, Long Beach, CA, USA, Feb, 25-29, 2024.

M. Novak, and S. Sahoo, ” Introduction to Classification Algorithms in Machine Learning, Carbon Footprint and Energy Consumption of AI Algorithms”, presented at ENG After Hours workshop, Aalborg, DK, May, 7, 2024.

S. Sahoo, “Neurons in our Brain vs ANN: How different are they?”, Invited seminar, March, 7, 2024