About
Contact & Profiles
A5005694627
Research Areas
- Advancements in Battery Materials
- Advanced Battery Technologies Research
- Electric Vehicles and Infrastructure
- Reliability and Maintenance Optimization
- Advanced Sensor and Control Systems
- Advanced Algorithms and Applications
Beihang University
2024-2025
Fuzhou University
2025
For the intricate and infrequent safety issues of batteries, online fault diagnosis over stochastic working conditions is indispensable. In this work, we employ deep learning methods to develop an network for lithium-ion batteries operating under unpredictable conditions. The integrates battery model constraints employs a framework designed manage evolution systems, thereby enabling real-time determination. We evaluate performance using dataset 18.2 million valid entries from 515 vehicles....
10.1038/s41467-025-56832-8
article
EN
cc-by-nc-nd
Nature Communications
2025-02-14
10.1016/j.energy.2024.132782
article
EN
Energy
2024-08-08
10.1109/icpeca63937.2025.10928802
article
EN
2025-01-17
10.1016/j.isatra.2024.12.034
article
EN
ISA Transactions
2024-12-01
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