Abstract | ||
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Cell-to-cell variability of batteries is a well-known problem especially when it comes to assembling large battery packs. Different battery cells exhibit substantial variability among them due to manufacturing tolerances, which should be carefully assessed and managed. Although battery packs usually incorporate some cell balancing circuitry, it is supposed to balance cell voltages dynamically at the expense of bypassed (not stored) charge. In this paper, we address the issue of how to consider variability when building battery packs based on a recently introduced combined cell-to-cell variation model of the capacity and of the internal resistance of a Li-Ion battery that accounts for variability effects in the cell manufacturing process. We attempt to figure out what kind of pack-level variability should be managed to reduce the cost of the cell balancing. We qualitatively evaluate inter- and intra-column variance minimizing cell placement approaches from the perspective of the passive cell balancing cost while considering the correlation between capacity and internal resistance. The intra-column minimization approach reduce the charging time and bypassed current by differentiating the column currents. |
Year | DOI | Venue |
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2014 | 10.1145/2593069.2596689 | DAC |
Keywords | Field | DocType |
model validation and analysis,variation-aware battery management,peukert's law,algorithms,design,constant current - constant voltage,model development,pack-level variability,battery management systems,statistical battery models,datasheet,constant current - constant voltage (cc-cv),combined cell-to-cell variation model,cell balancing cost reduction,intra-column minimization approach,passive cell balancing cost,internal resistance,management,cell manufacturing process,battery packs,secondary cells,battery modeling,lithium-ion battery,computational modeling,resistance,peukert s law,solid modeling | Computer science,Internal resistance,Voltage,Electronic engineering,Minification,Peukert's law,Battery (electricity),Manufacturing process,Datasheet | Conference |
ISSN | Citations | PageRank |
0738-100X | 4 | 0.48 |
References | Authors | |
2 | 3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Donghwa Shin | 1 | 396 | 32.34 |
Enrico Macii | 2 | 2405 | 349.96 |
Massimo Poncino | 3 | 125 | 18.57 |