2018
DOI: 10.1109/tec.2018.2850853
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An Optimization Framework for Dynamically Reconfigurable Battery Systems

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Cited by 33 publications
(20 citation statements)
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“…When it is desired to optimize the overall system performance across successive control periods, as in [34], [38], [42], [44], and [59], the system evolution has to be considered, including the time-varying OCVs, SoCs, and total available charge or energy of the cells. To take this into account, a dynamic system model needs to be appended to the optimization problem as a constraint.…”
Section: Optimization Algorithms Based On Reconfigurationmentioning
confidence: 99%
“…When it is desired to optimize the overall system performance across successive control periods, as in [34], [38], [42], [44], and [59], the system evolution has to be considered, including the time-varying OCVs, SoCs, and total available charge or energy of the cells. To take this into account, a dynamic system model needs to be appended to the optimization problem as a constraint.…”
Section: Optimization Algorithms Based On Reconfigurationmentioning
confidence: 99%
“…When it is desired to optimize the overall system performance across successive control periods, as in [34,38,42,44,59], the system evolution over these periods has to be considered, such as the time-varying OCVs, SoCs, and total available charge or energy of the cells. To take this into account, a dynamic system model has to be appended to the optimization problem as a constraint.…”
Section: B Optimization Algorithms Based On Reconfigurationmentioning
confidence: 99%
“…The problems proposed in [34,42,44,59] are all solved by DP, a common tool for solving multistage optimization problems. When solving these optimal control problems formulated for RBSs, the computational time and memory requirements are influenced by a number of factors, such as the system dimension, model nonlinearity, number of feasible configurations, and control horizon.…”
Section: B Optimization Algorithms Based On Reconfigurationmentioning
confidence: 99%
“…The battery temperature management is another task in charge of a BMS, usually carried out by activating fans for the battery cooling or even heaters, when the battery operates at very low temperatures and needs to be pre-heated before being fully operational. BMSs are sometimes also asked to dynamically manage the battery architecture [54,55], by controlling the parallelization of battery strings when the battery architecture is modular, and the battery capacity in ampere-hour can be selected and adapted to the application requirements by choosing the number of strings to be connected in parallel. Even part of the battery module series, that increase the battery voltage, can be excluded by the BMS with a bypass switch, in order to allow the module substitution or maintenance without interrupting the energy storage service [56].…”
Section: Energy Storage System Technologies For Micro-gridsmentioning
confidence: 99%