Constrained Ensemble Kalman Filter for Distributed Electrochemical State Estimation of Lithium-Ion Batteries
This article proposes a novel model-based estimator for distributed electrochemical states of lithium-ion (Li-ion) batteries. Through systematic simplifications of a high-order electrochemical-thermal coupled model consisting of partial differential-algebraic equations, a reduced-order battery model...
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| Veröffentlicht in: | IEEE transactions on industrial informatics Jg. 17; H. 1; S. 240 - 250 |
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| Sprache: | Englisch |
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Piscataway
IEEE
01.01.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 1551-3203, 1941-0050, 1941-0050 |
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| Abstract | This article proposes a novel model-based estimator for distributed electrochemical states of lithium-ion (Li-ion) batteries. Through systematic simplifications of a high-order electrochemical-thermal coupled model consisting of partial differential-algebraic equations, a reduced-order battery model is obtained, which features an equivalent circuit form and captures local state dynamics of interest inside the battery. Based on the physics-based equivalent circuit model, a constrained ensemble Kalman filter (EnKF) is pertinently designed to detect internal variables, such as the local concentrations, overpotential, and molar flux. To address slow convergence issues due to weak observability of the battery model, the Li-ion's mass conservation is judiciously considered as a constraint in the estimation algorithm. The estimation performance is comprehensively examined under a wide operating range. It demonstrates that the proposed EnKF-based nonlinear estimator is able to accurately reproduce the physically meaningful state variables at a low computational cost and is significantly superior to its prevalent benchmarks for online applications. |
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| AbstractList | This article proposes a novel model-based estimator for distributed electrochemical states of lithium-ion (Li-ion) batteries. Through systematic simplifications of a high-order electrochemical-thermal coupled model consisting of partial differential-algebraic equations, a reduced-order battery model is obtained, which features an equivalent circuit form and captures local state dynamics of interest inside the battery. Based on the physics-based equivalent circuit model, a constrained ensemble Kalman filter (EnKF) is pertinently designed to detect internal variables, such as the local concentrations, overpotential, and molar flux. To address slow convergence issues due to weak observability of the battery model, the Li-ion's mass conservation is judiciously considered as a constraint in the estimation algorithm. The estimation performance is comprehensively examined under a wide operating range. It demonstrates that the proposed EnKF-based nonlinear estimator is able to accurately reproduce the physically meaningful state variables at a low computational cost and is significantly superior to its prevalent benchmarks for online applications. |
| Author | Vilathgamuwa, Don Mahinda Li, Yang Zou, Changfu Xie, Changjun Wei, Zhongbao Xiong, Binyu |
| Author_xml | – sequence: 1 givenname: Yang orcidid: 0000-0002-9497-3051 surname: Li fullname: Li, Yang email: yang.li@whut.edu.cn organization: School of Automation, Wuhan University of Technology, Wuhan, China – sequence: 2 givenname: Binyu orcidid: 0000-0002-4156-2187 surname: Xiong fullname: Xiong, Binyu email: bxiong2@whut.edu.cn organization: School of Automation, Wuhan University of Technology, Wuhan, China – sequence: 3 givenname: Don Mahinda orcidid: 0000-0003-0895-8443 surname: Vilathgamuwa fullname: Vilathgamuwa, Don Mahinda email: mahinda.vilathgamuwa@qut.edu.au organization: School of Electrical Engineering and Robotics, Queensland University of Technology, Brisbane, QLD, Australia – sequence: 4 givenname: Zhongbao orcidid: 0000-0003-0051-5648 surname: Wei fullname: Wei, Zhongbao email: weizb@bit.edu.cn organization: National Engineering Laboratory for Electric Vehicles, School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China – sequence: 5 givenname: Changjun orcidid: 0000-0002-2532-9924 surname: Xie fullname: Xie, Changjun email: jackxie@whut.edu.cn organization: School of Automation, Wuhan University of Technology, Wuhan, China – sequence: 6 givenname: Changfu orcidid: 0000-0001-7119-6854 surname: Zou fullname: Zou, Changfu email: changfu.zou@chalmers.se organization: Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden |
| BackLink | https://research.chalmers.se/publication/520086$$DView record from Swedish Publication Index (Chalmers tekniska högskola) |
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| SubjectTerms | Algorithms Circuit design Computational modeling Constraints Differential equations Electrodes Ensemble Kalman filter (EnKF) Equivalent circuits Integrated circuit modeling Kalman filters Lithium lithium-ion (Li-ion) batteries Lithium-ion batteries Mathematical model Observability (systems) physics-based equivalent circuit model (PB-ECM) Rechargeable batteries Reduced order models State estimation |
| Title | Constrained Ensemble Kalman Filter for Distributed Electrochemical State Estimation of Lithium-Ion Batteries |
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