Journal of Power Electronics

  • 제18권4호
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  • Pages.1127-1139
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  • 2018
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  • 1598-2092(pISSN)
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  • 2093-4718(eISSN)
전력전자학회 (The Korean Institute of Power Electronics)
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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)
  • 투고 : 2017.11.03
  • 심사 : 2018.03.01
  • 발행 : 2018.07.20
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초록

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.

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