The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Estimation of Battery State of Charge With $H_{\infty}$ Observer: Applied to a Robot for Inspecting Power Transmission Lines
Abstract
Battery state-of-charge (SOC) estimation is essential for a mobile robot, such as inspection of power transmission lines. It is often estimated using a Kalman filter (KF) under the assumption that the statistical properties of the system and measurement errors are known. Otherwise, the SOC estimation error may be large or even divergent. In this paper, without the requirement of the known statistical properties, a SOC estimation method is proposed using anH∞observer, which can still guarantee the SOC estimation accuracy in the worst statistical error case. Under the conditions of different currents and temperatures, the effectiveness of the proposed method is verified in the laboratory and field environments. With the comparison of the proposed method and the KF-based one, the experimental results show that the proposed method can still provide accurate SOC estimation when there exist inexact or unknown statistical properties of the errors. The proposed method has been applied successfully to the robot for inspecting the running 500-kV extra high voltage power transmission lines.
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Citations
Cites
Ng, K. S., Moo, C.-S., Chen, Y.-P., & Hsieh, Y.-C. (2009) · Applied Energy · doi:10.1016/j.apenergy.2008.11.021 · Cited by 1,636
Sun, F., Hu, X., Zou, Y., & Li, S. (2011) · Energy · doi:10.1016/j.energy.2011.03.059 · Cited by 614
Cited by
Waag, W., Fleischer, C., & Sauer, D. U. (2014) · Journal of Power Sources · doi:10.1016/j.jpowsour.2014.02.064 · Cited by 1,059
Hu, X., Jiang, J., Cao, D., & Egardt, B. (2015) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2015.2461523 · Cited by 504
Advanced Machine Learning Approach for Lithium-Ion Battery State Estimation in Electric Vehicles
Hu, X., Li, S. E., & Yang, Y. (2016) · IEEE Transactions on Transportation Electrification · doi:10.1109/tte.2015.2512237 · Cited by 375
The State of Charge Estimation of Lithium-Ion Batteries Based on a Proportional-Integral Observer
Xu, J., Mi, C. C., Cao, B., Deng, J., Chen, Z., & Li, S. (2014) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2013.2287375 · Cited by 367
Chen, C., Xiong, R., & Shen, W. (2018) · IEEE Transactions on Power Electronics · doi:10.1109/tpel.2017.2670081 · Cited by 295
Metadata
- Authors
- Zhang, F., Liu, G., Fang, L., & Wang, H.
- Venue
- IEEE Transactions on Industrial Electronics
- Published
- 2012-02
- Volume
- 59
- Issue
- 2
- Pages
- 1086-1095
- ISSN
- 0278-0046 (ISSN-L)
- 1557-9948
- OpenAlex
- W2137804106
- Cited by
- 171
- References
- 2
- FWCI
- 24.92
- Type
- journal article
- Language
- en
- Open access
- closed
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- Zhang, F., Liu, G., Fang, L., & Wang, H. (2012). Estimation of Battery State of Charge With $H_{\infty}$ Observer: Applied to a Robot for Inspecting Power Transmission Lines. IEEE Transactions on Industrial Electronics. https://doi.org/10.1109/tie.2011.2159691
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