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Large Models for Battery Prognostics and Health Management: A Review and Future Roadmap
Transformerself-supervised learningbattery managementdata ecosystems
2608.26111
Builder Relevance
1h ago80%
Abstract
This paper reviews the application of Large Models in Battery Prognostics and Health Management, highlighting their potential to overcome traditional challenges in the field.
Reality Card
Core Claim
Large Models built on Transformer architectures can significantly improve Battery Prognostics and Health Management by addressing issues such as data scarcity and model interpretability.
Method / Result
The review categorizes progress in four dimensions, including enhancing generalization and robustness.
Limitations
Challenges remain in data accessibility, intelligence validation, and deployment feasibility.
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