Distributed event‐triggered algorithms for the management of networked battery systems

Distributed algorithms have recently been developed for a networked battery system composed of multiple battery units, each of which serves as an energy storage unit. These emerging distributed algorithms rely on continuous communication among battery units and/or continuous update of power allocati...

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Vydáno v:International journal of robust and nonlinear control Ročník 35; číslo 17; s. 7041 - 7066
Hlavní autoři: Qian, Yangyang, Meng, Tingyang, Lin, Zongli, Wan, Yan, Shamash, Yacov A.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Hoboken, USA John Wiley & Sons, Inc 25.11.2025
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ISSN:1049-8923, 1099-1239
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Abstract Distributed algorithms have recently been developed for a networked battery system composed of multiple battery units, each of which serves as an energy storage unit. These emerging distributed algorithms rely on continuous communication among battery units and/or continuous update of power allocation for each battery unit. To reduce the communication and computational burden, we propose distributed event‐triggered algorithms for the management of networked battery systems with unknown battery unit parameters. In particular, two event‐triggered distributed estimators are designed for each battery unit to respectively estimate the average battery unit state and the average desired power with any specified level of accuracy. Two dynamic event‐triggering mechanisms are proposed for the distributed estimators that determine when each battery unit communicates with its neighbors. Based on these two event‐triggered distributed estimators, an event‐triggered distributed adaptive power allocating law along with a static event‐triggering mechanism is designed for each battery unit to update the power allocation in a discrete‐time manner. It is shown that the proposed power allocating laws achieve state‐of‐charge balancing among all battery units while delivering the desired total power in either the charging or discharging mode without requiring either continuous communication or continuous update of power allocation. It is also shown that the Zeno behavior is excluded for all the three event‐triggering mechanisms. A simulation example is provided to validate the effectiveness of the proposed design.
AbstractList Distributed algorithms have recently been developed for a networked battery system composed of multiple battery units, each of which serves as an energy storage unit. These emerging distributed algorithms rely on continuous communication among battery units and/or continuous update of power allocation for each battery unit. To reduce the communication and computational burden, we propose distributed event‐triggered algorithms for the management of networked battery systems with unknown battery unit parameters. In particular, two event‐triggered distributed estimators are designed for each battery unit to respectively estimate the average battery unit state and the average desired power with any specified level of accuracy. Two dynamic event‐triggering mechanisms are proposed for the distributed estimators that determine when each battery unit communicates with its neighbors. Based on these two event‐triggered distributed estimators, an event‐triggered distributed adaptive power allocating law along with a static event‐triggering mechanism is designed for each battery unit to update the power allocation in a discrete‐time manner. It is shown that the proposed power allocating laws achieve state‐of‐charge balancing among all battery units while delivering the desired total power in either the charging or discharging mode without requiring either continuous communication or continuous update of power allocation. It is also shown that the Zeno behavior is excluded for all the three event‐triggering mechanisms. A simulation example is provided to validate the effectiveness of the proposed design.
Author Qian, Yangyang
Meng, Tingyang
Shamash, Yacov A.
Lin, Zongli
Wan, Yan
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  givenname: Yacov A.
  surname: Shamash
  fullname: Shamash, Yacov A.
  organization: Stony Brook University
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CitedBy_id crossref_primary_10_1109_TNSE_2024_3434957
crossref_primary_10_1016_j_est_2024_114550
crossref_primary_10_1080_00207721_2025_2534901
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Snippet Distributed algorithms have recently been developed for a networked battery system composed of multiple battery units, each of which serves as an energy...
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SubjectTerms Algorithms
Communication
consensus
distributed estimation
distributed event‐triggered algorithms
Estimators
networked battery systems
nonlinear dynamics
Power management
state‐of‐charge balancing
Storage units
Title Distributed event‐triggered algorithms for the management of networked battery systems
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https://www.proquest.com/docview/3265610877
Volume 35
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