The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.
Remaining Useful Life Prediction of Lithium-Ion Batteries Based on Spherical Cubature Particle Filter
Abstract
Lithium-ion batteries are critical components to provide power sources for commercial products. To ensure a high reliability of lithium-ion batteries, prognostic actions for lithium-ion batteries should be prepared. In this paper, a prognostic method is proposed to predict the remaining useful life (RUL) of lithium-ion batteries. A state-space model for the lithium-ion battery capacity is first constructed to assess capacity degradation. Then, a spherical cubature particle filter (SCPF) is introduced to solve the state-space model. The major idea of the SCPF is to adapt a spherical cubature integration-based Kalman filter to provide an importance function of a standard particle filter (PF). Once the state-space model is determined, the extrapolations of the state-space model to a specified failure threshold are performed to infer the RUL of the lithium-ion batteries. Degradation data of 26 lithium-ion battery capacities were analyzed to validate the effectiveness of the proposed prognostic method. The analytical results show that the proposed prognostic method is more effective in the prediction of RUL of lithium-ion batteries, compared with an existing PF-based prognostic method.
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Metadata
- Authors
- Wang, D., Yang, F., Tsui, K.-L., Zhou, Q., & Bae, S. J.
- Venue
- IEEE Transactions on Instrumentation and Measurement
- Published
- 2016-06
- Volume
- 65
- Issue
- 6
- Pages
- 1282-1291
- ISSN
- 0018-9456 (ISSN-L)
- 1557-9662
- OpenAlex
- W2333401465
- Cited by
- 287
- References
- 45
- FWCI
- 20.22
- Type
- journal article
- Language
- en
- Open access
- closed
- Funders
- General Research Fund of City University of Hong Kong (11216014)
- National Natural Science Foundation of China (11471275, 51505307)
- Research Grants Council Theme-Based Research Scheme (T32-101/15-R)
- Human Resources Program in Energy Technology of the Korea Institute of Energy Technology Evaluation and Planning within the Ministry of Trade, Industry and Energy, South Korea (20154030200900)
- Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education (201500000002571)
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- Wang, D., Yang, F., Tsui, K.-L., Zhou, Q., & Bae, S. J. (2016). Remaining Useful Life Prediction of Lithium-Ion Batteries Based on Spherical Cubature Particle Filter. IEEE Transactions on Instrumentation and Measurement. https://doi.org/10.1109/tim.2016.2534258
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