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Bandwidth-Increased Ripple-Mitigating Scheduling Algorithm for Dynamically Reconfigurable Batteries
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DOI：10.1109/ACCESS.2022.3204058.png)
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摘要
En 中文
Modular cascaded circuits offer attractive qualities in reconfigurable battery applications, including improved fault tolerance and flexibility. In contrast to conventional hard-wired dc battery packs, however, cascaded topologies, such as modular multilevel circuits (MMC) with serial or serial and parallel connectivity, load modules with substantial low-frequency current ripple, which generates additional loss and can accelerate battery aging. Recent studies reveal that low-frequency ripple can cause noticeable battery aging, whereas high frequencies are insignificant, presumably mainly as they can be absorbed by the dielectric electrode capacitance, and reduce heating associated with lower high-frequency battery impedance. Previous MMC-battery control methods solely focus on state-of-charge and thermal balancing of individual modules, while the few existing methods for suppressing ripple tend to form low-frequency patterns in the modules' load, which increase battery cycling as well as loss. This paper presents a ripple-oriented high-bandwidth control technique that minimizes low-frequency components in the module load spectrum and improves battery treatment, while maintaining the average switching frequency. The control method takes limitations related to module data acquisition into account and enhances the feedback bandwidth using observers. It works with a wide range of topologies including modules with series connectivity only as well as series/parallel. The measurements in the laboratory verify the shift of the module load from the 10 - 100 Hz range to similar to 5 kHz and a reduction of battery losses by up to 20 %.
Keyword:
Modular battery
modular multilevel converter
cascaded bridge converter
reconfigurable battery
battery ageing model
ripple suppression
influence of ripple current
second harmonic
scheduling
battery energy storage systems (BESS)
electric vehicle drive trains
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
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