Active Balancing of Lithium-Ion Batteries Using Graph Theory and A-Star Search Algorithm

The heterogeneity of cells in a battery pack is inevitable but brings high risks of premature failure and even safety hazards. Accordingly, for safe and long-life operation, it is necessary to adjust the state of charge (SOC) of all in-pack cells to the same level. To address this problem, this arti...

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Vydáno v:IEEE transactions on industrial informatics Ročník 17; číslo 4; s. 2587 - 2599
Hlavní autoři: Dong, Guangzhong, Yang, Fangfang, Tsui, Kwok-Leung, Zou, Changfu
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 01.04.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Balancing
Batteries
Cell balancing
Energy dissipation
Equalization
Estimation
Graph theory
Heterogeneity
Ice
Integrated circuit modeling
Liapunov direct method
Lithium
Lithium-ion batteries
lithium-ion battery
parallel operation
power converter
Pulse width modulation
Rechargeable batteries
Search algorithms
Shortest-path problems
Stability analysis
state estimation
State of charge
Topology
ISSN:1551-3203, 1941-0050, 1941-0050
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Shrnutí:The heterogeneity of cells in a battery pack is inevitable but brings high risks of premature failure and even safety hazards. Accordingly, for safe and long-life operation, it is necessary to adjust the state of charge (SOC) of all in-pack cells to the same level. To address this problem, this article first proposes a battery SOC observer and analyzes its stability and convergence analysis using the Lyapunov direct method. Different to most available estimators is that the proposed method does not require the information of cell capacities. Then, after modeling the equalization system as a directed graph, the equalization problem is cast as a path searching problem. Finally, an A-star algorithm subject to balancing constraints is proposed to find the shortest path in this graph, corresponding to the most efficient SOC equalization. Experimental results show that the steady-state error of the proposed observer is less than <inline-formula><tex-math notation="LaTeX">2\%</tex-math></inline-formula>. It also demonstrates that the A-star algorithm can decrease the balancing time and energy loss during the balancing process by 9.59% and 19.5%, respectively, relative to the mean-difference-average method.
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ISSN:1551-3203
1941-0050
1941-0050
DOI:10.1109/TII.2020.2997828