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http://dx.doi.org/10.6113/JPE.2018.18.4.1127

Adaptive State-of-Charge Estimation Method for an Aeronautical Lithium-ion Battery Pack Based on a Reduced Particle-unscented Kalman Filter  

Wang, Shun-Li (School of Information Engineering and Robot Technology Used for Special Environment Key Laboratory of Sichuan Province, Southwest University of Science and Technology)
Yu, Chun-Mei (School of Information Engineering and Robot Technology Used for Special Environment Key Laboratory of Sichuan Province, Southwest University of Science and Technology)
Fernandez, Carlos (School of Pharmacy and Life Sciences, Robert Gordon University)
Chen, Ming-Jie (School of Information Engineering and Robot Technology Used for Special Environment Key Laboratory of Sichuan Province, Southwest University of Science and Technology)
Li, Gui-Lin (School of Information Engineering and Robot Technology Used for Special Environment Key Laboratory of Sichuan Province, Southwest University of Science and Technology)
Liu, Xiao-Han (School of Information Engineering and Robot Technology Used for Special Environment Key Laboratory of Sichuan Province, Southwest University of Science and Technology)
Publication Information
Journal of Power Electronics / v.18, no.4, 2018 , pp. 1127-1139 More about this Journal
Abstract
A reduced particle-unscented Kalman filter estimation method, along with a splice-equivalent circuit model, is proposed for the state-of-charge estimation of an aeronautical lithium-ion battery pack. The linearization treatment is not required in this method and only a few sigma data points are used, which reduce the computational requirement of state-of-charge estimation. This method also improves the estimation covariance properties by introducing the equilibrium parameter state of balance for the aeronautical lithium-ion battery pack. In addition, the estimation performance is validated by the experimental results. The proposed state-of-charge estimation method exhibits a root-mean-square error value of 1.42% and a mean error value of 4.96%. This method is insensitive to the parameter variation of the splice-equivalent circuit model, and thus, it plays an important role in the popularization and application of the aeronautical lithium-ion battery pack.
Keywords
Lithium-ion battery pack; Reduced particle-unscented Kalman filter; Splice-equivalent circuit model; State of balance; State-of-charge estimation;
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Times Cited By KSCI : 4  (Citation Analysis)
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