An Innovative State-of-charge Estimation Method of Lithium-ion Battery Based on 5th-order Cubature Kalman Filter
Author:
Funder
National Key Research and Development Program of China
Publisher
Springer Science and Business Media LLC
Subject
Automotive Engineering
Link
https://link.springer.com/content/pdf/10.1007/s42154-021-00162-0.pdf
Reference30 articles.
1. Lai, X., Qin, C., Gao, W., et al.: A state of charge estimator based extended Kalman filter using an electrochemistry-based equivalent circuit model for lithium-ion batteries. Appl. Sci. 8, 1592 (2018)
2. Xia, B., Zhen, S., Zeng, R.F., et al.: A cubature particle filter algorithm to estimate the state of the charge of lithium-ion batteries based on a second-order equivalent circuit model. Energies 10, 457–472 (2017)
3. Wahyuddin, I., Priambodo, P., Sudibyo, H. (2018) State of charge (SoC) analysis and modeling battery discharging parameters. In: Paper presented at the 4th Int Conf Sci Technol, Yogyakarta
4. Li, S., Li, J., Huang, H.W., Wang, H.: Lithium-ion battery modeling based on big data. Energy Proced. 159, 168–173 (2019)
5. Chen, Z., Sun, H., Dong, G., et al.: Particle filter-based state-of-charge estimation and remaining-dischargeable-time prediction method for lithium-ion batteries. J. Power Sources 414, 158–166 (2019)
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