Increase lifespan with a cell management algorithm in electric energy storage systems

Savard, Christophe; Venet, Pascal; Praly, Laurent; Niel, Éric; Sarı, Ali

doi:10.1109/icit.2018.8352447

Cited by 3 publications

(5 citation statements)

References 19 publications

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“…Operative dependability for the variants are relative compared (base 100 for basic PS) in the bar graph in Figure 12, drawn for a (3,4) structure. Thus, the performances can be grouped into three clusters: those that are between 100% and 120% of the basic PS operative dependability, those between 120% and 140%, and those higher [30]. Among the less powerful variants are the classic solutions: balancing in SP architecture, redundancy, fault tolerance and over-capacity.…”

Section: Results and Comparisonsmentioning

confidence: 99%

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Comparison of Battery Architecture Dependability

et al. 2018

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This paper presents various solutions for organizing an accumulator battery. It examines three different architectures: series-parallel, parallel-series and C3C architecture, which spread the cell output current flux to three other cells. Alternatively, to improve a several cell system reliability, it is possible to insert more cells than necessary and soliciting them less. Classical RAMS (Reliability, Availability, Maintainability, Safety) solutions can be deployed by adding redundant cells or by tolerating some cell failures. With more cells than necessary, it is also possible to choose active cells by a selection algorithm and place the others at rest. Each variant is simulated for the three architectures in order to determine the impact on battery-operative dependability, that is to say the duration of how long the battery complies specifications. To justify that the conventional RAMS solutions are not deployed to date, this article examines the influence on operative dependability. If the conventional variants allow to extend the moment before the battery stops to be operational, using an algorithm with a suitable optimization criterion further extend the battery mission time.Batteries 2018, 4, 31 2 of 12 seen in Figure 1. In this, a cell is represented as a series association of an open-circuit voltage (OCV), an equivalent series resistance (ESR) and a parallel RC circuit. The ESR corresponds to the battery terminals voltage V cell , only if it is measured without an external load connection and with the cell at rest for an adequate time. This time is necessary for balancing internal electrical charges (relaxation phenomenon). A double-layer capacitance (C w ) and a charge transfer resistance (R w ) complete the model by describing relaxation. Other internal phenomena such as a hysteresis voltage can also be modeled by additional subcircuits. Hysteresis consists in a shifting on the open-circuit voltage for the same contained charge between current direction, an upward offset with a negative current I cell in charging phase and a downset offset with a positive current in the discharge phase.Batteries 2018, 4, x FOR PEER REVIEW 2 of 12 an equivalent series resistance (ESR) and a parallel RC circuit. The ESR corresponds to the battery terminals voltage Vcell, only if it is measured without an external load connection and with the cell at rest for an adequate time. This time is necessary for balancing internal electrical charges (relaxation phenomenon). A double-layer capacitance (Cw) and a charge transfer resistance (Rw) complete the model by describing relaxation. Other internal phenomena such as a hysteresis voltage can also be modeled by additional subcircuits. Hysteresis consists in a shifting on the open-circuit voltage for the same contained charge between current direction, an upward offset with a negative current Icell in charging phase and a downset offset with a positive current in the discharge phase.

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Section: Results and Comparisonsmentioning

confidence: 99%

“…between 120% and 140%, and those higher [30]. Among the less powerful variants are the classic solutions: balancing in SP architecture, redundancy, fault tolerance and over-capacity.…”

Section: Results and Comparisonsmentioning

confidence: 99%

Comparison of Battery Architecture Dependability

et al. 2018

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“…Another way to organize the cells inside a battery is to use the C3C architecture [6,52], in which each cell of row i and column j is associated by its node a upstream with the three cells from the row i − 1 and columns j − 1 , j and j + 1 . Similarly, this cell is associated downstream with the cells of the row i + 1 and the same three columns by their nodes b, Fig.…”

Section: Battery Modelmentioning

confidence: 99%

Comparing lithium-ion battery architecture performances with Colored Petri Net

Savard¹,

Praly

Venet

et al. 2019

SN Appl. Sci.

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Conventionally, the basic cells constituting the multicellular energy storage systems are modeled by electrical schemes based on Thevenin's model. Other, more complex models incorporate the aging phenomena, resulting in a decrease in the State of Health of each cell. All these models remain analytical models and not discrete event systems. In this article, a discrete model is proposed, by detailing how each physical parameter is modeled. It is based on a no-timed Colored High-Level Petri Net. An example of a battery is simulated to validate this theoretical model. Its structure (number of cells) is declined under different architectures (connections between the cells) and is subjected to different resource dynamic allocation strategies. This Petri Net (PN) model makes easy, by adding a sub-network, to simulate different control laws and different resource management algorithms, whether or not allow commutations by forbiding all configurations that do not meet the specification or that will lead to accelerated cell aging. PN is used as a tool for comparing hardware architectures and cell control logic for a battery. Various conventional and innovative architecture are simulate. Different control laws can be compared in terms of performance, as lifespan and use of resources.

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“…The different ways of arranging the cells in a battery, in order to meet the external load specifications, have already been the subject of several publications [42][43][44][45][46]. Their respective reliability has been analyzed in [30].…”

Section: Cell Associationmentioning

confidence: 99%

“…This means that, for a normal use, all the active cells are maximally solicited at their nominal current. It has been shown in [46], that added spare cells would not improve lifespan unless resources are dynamically driven. On the other hand, by means of serial or parallel connections between cells, these connected cells share either the same current or the same voltage.…”

Section: Cell Associationmentioning

confidence: 99%

Insert Switches Inside to Increase Battery Lifespan

Savard¹,

Venet²,

Niel³

et al. 2020

EJERS

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This paper shows the possible gain on time before the end of useful time brought by switches addition in a multicell battery. In a first time, it presents a battery electric model. A battery includes many identical electrical energy cells that electrically interact. From a behavioral standpoint, cell performance is measured by fundamental parameters: State of Charge (SoC) and State of Health (SoH). To simulate cell electrical behavior, the Thevenin model or the Nernst model are often used. However, these models do not take into account the cells aging or the possible interactions on aging. A cell ages mainly in two ways: cyclic and calendar. This aging impacts both the elements of the equivalent electrical model and the fundamental parameters (SoC and SoH). Thus, the conventional electric model of a cell does not accurately reflect the cell aging. In this paper, another formal model based on the fundamental curve that relates electrical and behavioral parameters is proposed. It integrates aging into the equivalent electric model estimation. In a second time, in order to validate this model, this cell model is used to simulate parallel-series association. To improve battery lifespan, in addition to the usual balancing techniques, it may be relevant to require some traditional reliability and operating safety solutions. This requires to add switches inside battery. The presented simulation shows adding switches solution is currently not deployed. This is justified in this paper by examining the impact provide on lifespan improvement on an example, which is pretty weak. But it also shows that however, by managing active cells in a different way, adding switches and spare cells can really reach this improvement.

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Increase lifespan with a cell management algorithm in electric energy storage systems

Cited by 3 publications

References 19 publications

Comparison of Battery Architecture Dependability

Comparison of Battery Architecture Dependability

Comparing lithium-ion battery architecture performances with Colored Petri Net

Insert Switches Inside to Increase Battery Lifespan

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