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RISS 인기검색어
- 검색키워드
- 저자 : Davor Zorc (검색결과 3 건)
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Dual EKF-Based State and Parameter Estimator for a LiFePO₄ Battery Cell
Danijel Pavkovi?,Matija Krznar,Ante Komljenovi?,Mario Hrgeti?,Davor Zorc 전력전자학회 2017 JOURNAL OF POWER ELECTRONICS Vol.17 No.2
This work presents the design of a dual extended Kalman filter (EKF) as a state/parameter estimator suitable for adaptive state-of-charge (SoC) estimation of an automotive lithium–iron–phosphate (LiFePO₄) cell. The design of both estimators is based on an experimentally identified, lumped-parameter equivalent battery electrical circuit model. In the proposed estimation scheme, the parameter estimator has been used to adapt the SoC EKF-based estimator, which may be sensitive to nonlinear map errors of battery parameters. A suitable weighting scheme has also been proposed to achieve a smooth transition between the parameter estimator-based adaptation and internal model within the SoC estimator. The effectiveness of the proposed SoC and parameter estimators, as well as the combined dual estimator, has been verified through computer simulations on the developed battery model subject to New European Driving Cycle (NEDC) related operating regimes.
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Dual EKF-Based State and Parameter Estimator for a LiFePO<sub>4</sub> Battery Cell
Pavkovic, Danijel,Krznar, Matija,Komljenovic, Ante,Hrgetic, Mario,Zorc, Davor The Korean Institute of Power Electronics 2017 JOURNAL OF POWER ELECTRONICS Vol.17 No.2
This work presents the design of a dual extended Kalman filter (EKF) as a state/parameter estimator suitable for adaptive state-of-charge (SoC) estimation of an automotive lithium-iron-phosphate ($LiFePO_4$) cell. The design of both estimators is based on an experimentally identified, lumped-parameter equivalent battery electrical circuit model. In the proposed estimation scheme, the parameter estimator has been used to adapt the SoC EKF-based estimator, which may be sensitive to nonlinear map errors of battery parameters. A suitable weighting scheme has also been proposed to achieve a smooth transition between the parameter estimator-based adaptation and internal model within the SoC estimator. The effectiveness of the proposed SoC and parameter estimators, as well as the combined dual estimator, has been verified through computer simulations on the developed battery model subject to New European Driving Cycle (NEDC) related operating regimes.
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Dual EKF-Based State and Parameter Estimator for a LiFePO4 Battery Cell
Danijel Pavković,Matija Krznar,Ante Komljenović,Mario Hrgetić,Davor Zorc 전력전자학회 2017 JOURNAL OF POWER ELECTRONICS Vol.17 No.2
This work presents the design of a dual extended Kalman filter (EKF) as a state/parameter estimator suitable for adaptive state-of-charge (SoC) estimation of an automotive lithium–iron–phosphate (LiFePO4) cell. The design of both estimators is based on an experimentally identified, lumped-parameter equivalent battery electrical circuit model. In the proposed estimation scheme, the parameter estimator has been used to adapt the SoC EKF-based estimator, which may be sensitive to nonlinear map errors of battery parameters. A suitable weighting scheme has also been proposed to achieve a smooth transition between the parameter estimator-based adaptation and internal model within the SoC estimator. The effectiveness of the proposed SoC and parameter estimators, as well as the combined dual estimator, has been verified through computer simulations on the developed battery model subject to New European Driving Cycle (NEDC) related operating regimes.
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