Abstract
In battery management systems (BMSs), state estimation stands as a pivotal element yet encounters significant challenges. These include the poor observability inherent in fixed configuration battery packs, limited generalizability of pre-trained machine learning models, and the deficiency of higher-level management strategies. To address these obstacles, we propose a forward-looking perspective on the future BMS state estimation, introducing the concept of a "Smart Battery". Battery digital twin enables synthetic data generation and physics-informed AI development. This approach integrates battery digital twin to generate synthetic data, which is then used for data augmentation and physics-informed AI development. Additionally, it incorporates advanced data cleaning and selection techniques to preserve essential information and augment data management efficiency. Leveraging cutting-edge AI algorithms, such as transfer learning and meta-learning, aims to mitigate issues of model generalization and feature invalidation under various operating conditions. Furthermore, this paper emphasizes the importance of multi-task learning for batteries, enabling comprehensive health assessments. By fully utilizing both short-term estimations and long-term predictions, the proposed framework contributes to the advancement of higher-level health and thermal management designs. We aim to furnish pioneering insights for state estimation in future intelligent BMSs.
Originalsprog | Engelsk |
---|---|
Titel | 2024 IEEE 10th International Power Electronics and Motion Control Conference, IPEMC 2024 ECCE Asia |
Antal sider | 5 |
Forlag | IEEE Signal Processing Society |
Publikationsdato | 2024 |
Sider | 5126-5130 |
ISBN (Elektronisk) | 9798350351330 |
DOI | |
Status | Udgivet - 2024 |
Begivenhed | 10th IEEE International Power Electronics and Motion Control Conference, IPEMC 2024 ECCE Asia - Chengdu, Kina Varighed: 17 maj 2024 → 20 maj 2024 |
Konference
Konference | 10th IEEE International Power Electronics and Motion Control Conference, IPEMC 2024 ECCE Asia |
---|---|
Land/Område | Kina |
By | Chengdu |
Periode | 17/05/2024 → 20/05/2024 |
Sponsor | China Electrotechnical Society (CES), IEEE Power Electronics Society (PELS), Southwest Jiaotong University |
Navn | 2024 IEEE 10th International Power Electronics and Motion Control Conference, IPEMC 2024 ECCE Asia |
---|
Bibliografisk note
Publisher Copyright:© 2024 IEEE.