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Yixiu Wang
Yixiu Wang is a PhD student studying Chemical and Biological Engineering (CHBE) at UBC. He received his bachelor's degree and master's degree in Vehicle Engineering/Automotive Electronics from Tongji University in China, where he worked on life equalization strategy for series battery pack to maximum discharge energy. His current research interests include applying machine learning techniques to develop lithium-ion battery degradation models to accurately estimate and predict power and capacity loss, and optimizing power system operation incorporating battery degradation.
📚 Program/Degree
GROUP ALUMNI (2024) |
PhD
| Started 2019
📝 Research
Modeling, Control and Optimization of Battery Systems
👥 Also supervised by
DAIS Lab Publications
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Conference Proceedings
Online Capacity Estimation of Lithium-ion Batteries by Partial Incremental Capacity Curve
Proceedings of the 19th IEEE Vehicle Power and Propulsion Conference (To Appear). 2022 [PDF] -
Journal Paper
Data-driven capacity estimation of commercial lithium-ion batteries from voltage relaxation
Nature Communications. 2022 [PDF] [Code] -
Journal Paper
Causal Discovery based on Observational Data and Process Knowledge in Industrial Processes
Industrial & Engineering Chemistry Research. 2022 [PDF] -
Journal Paper
Long Short-Term Memory Network with Transfer Learning for Lithium-ion Battery Capacity Fade and Cycle Life Prediction
Applied Energy. 2023 [PDF] -
Conference Proceedings
Interpretable Industrial Soft Sensor Design Based on Informer and SHAP
In Proceedings of the 12th IFAC International Symposium on Advanced Control of Chemical Processes (ADCHEM). 2024 [PDF] -
Conference Proceedings
Interpretable Data-Driven Capacity Estimation of Lithium-ion Batteries
In Proceedings of the 12th IFAC International Symposium on Advanced Control of Chemical Processes (ADCHEM). 2024 [PDF] -
Journal Paper
A Generalizable Method for Capacity Estimation and RUL Prediction in Lithium-Ion Batteries
Industrial and Engineering Chemistry Research. 2024 [PDF] -
Journal Paper
Real-Time Tracking of Renewable Carbon Content with AI-aided Approaches During Co-Processing of Biofeedstocks
Applied Energy. 2024 [PDF] -
Journal Paper
Data-driven battery capacity estimation using support vector regression and model bagging under fast-charging conditions
Canadian Journal Of Chemical Engineering. 2024 [PDF]
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