KR102549478B1 - Simulation Apparatus and Method for Flow Battery having Porous Electrode with Flow Channel - Google Patents

Abstract

The present invention is formed by a porous electrode in a flow battery and a flow channel for supplying the applied electrolyte to the porous electrode implemented in a predetermined pattern on one surface of the porous electrode to confirm the flow path structure of the flow path through which the electrolyte is delivered, According to the identified flow path structure, each of the porous electrode and the flow channel is divided based on a plurality of nodes having a predetermined distance interval, and a network model of a structure in which adjacent nodes among the plurality of divided nodes are connected by resistance that hinders electrolyte flow. The pressure drop in a closed loop consisting of a network model generation unit that generates a network model, and a flow rate flowing in and out of each of a plurality of nodes of the network model satisfies the law of conservation of mass, and a resistance connecting adjacent nodes among the plurality of nodes Apparatus and method for simulating a flow cell capable of rapidly analyzing a flow state in a stack of flow cells at low computational cost, including a network analyzer that calculates the flow rate and pressure drop between each node of the network model to satisfy the law of conservation of energy can provide.

Description

Simulation Apparatus and Method for Flow Battery having Porous Electrode with Flow Channel

The present invention relates to an apparatus and method for simulating a flow battery, and more particularly to an apparatus and method for simulating a flow battery having a flow channel and a porous electrode.

As the demand for renewable energy increases, interest in an energy storage system (ESS) that can efficiently store and manage it is also increasing. Existing ESS mainly used lithium-ion batteries, but due to problems such as harm to the human body and fire hazard, research on replacing them with flow batteries such as Vanadium Redox Flow Battery (VRFB) or fuel cells is active. is being carried out

Unlike lithium ion batteries, flow batteries such as vanadium redox flow batteries (VRFB) or fuel cells have a structure divided into stacks including electrodes and tanks functioning as electrolyte reservoirs, While a fluid or gaseous electrolyte (also referred to as an active material) stored in a tank circulates through at least one battery cell constituting the stack, a chemical reaction is generated at the interface of the porous electrode inside the battery cell to generate power. It happens. At this time, conventionally, the battery cell was configured so that the electrolyte passes through the entire porous electrode to cause a reaction, but recently, a stack is formed so that the electrolyte flowing into the porous electrode causes a reaction while flowing through a flow channel formed on one side of the porous electrode. this is composed

In a flow battery having a stack in which a flow channel is formed as described above, it is required to check the state of a fluid or gaseous electrolyte flowing along the flow channel. That is, analysis of the flow state of the electrolyte is very important in a flow battery having a flow channel and a porous electrode. However, fluid properties such as density and viscosity of active materials vary greatly, and the size and internal structure of battery cells vary greatly, so a flow state analysis suitable for a flow battery to be used must be performed. In the past, commercial tool-based computational fluid dynamics (CFD) simulations were mainly used for flow analysis. However, CFD simulation is performed by calculating the Navier-Sokes equation in the flow channel and porous electrode based on the Finite Difference Method (FDM) or the Finite Elements Method (FEM). Since the analysis is performed, the computation cost is very high, and there is a problem in that a high-performance computation device and a long computation time are required. Accordingly, there is a need for a new technique capable of quickly analyzing the flow characteristics of a flow battery in a conventional computing device at low computational cost.

Korean Registered Patent No. 10-2144745 (registered on August 10, 2020)

An object of the present invention is to provide a flow cell simulation device and method capable of quickly calculating electrolyte flow characteristics of a flow cell including a flow channel and a porous electrode at low cost.

Another object of the present invention is to provide an apparatus and method for simulating a flow battery with low computational cost so that it can be executed in a general battery management system with low computational performance.

A flow battery simulation device according to an embodiment of the present invention for achieving the above object is implemented in a porous electrode and a predetermined pattern on one surface of the porous electrode in a flow battery to supply an applied electrolyte to the porous electrode. The flow path structure of the flow path formed by the channel is confirmed, and according to the identified flow path structure, the porous electrode and the flow channel are divided based on a plurality of nodes having predetermined distance intervals, and the divided A network model generating unit for generating a network model of a structure in which adjacent nodes among a plurality of nodes are connected with resistance that hinders electrolyte flow; and a flow rate flowing in and out of each of a plurality of nodes of the network model satisfies the law of conservation of mass, and a pressure drop in a closed loop composed of resistors connecting adjacent nodes among the plurality of nodes satisfies the law of conservation of energy. , and a network analyzer for calculating the flow rate and pressure drop between each node of the network model.

The network model generation unit checks the porous electrode constituting the flow path and the flow channel structure, and according to the identified flow channel structure, decomposes the flow channel into a plurality of sections based on bending or branching positions, and among the divided sections A plurality of sections disposed parallel to each other are again divided into predetermined channel length units, and the region of the porous electrode is divided according to an electrode length set corresponding to the channel length and a distance between a plurality of sections disposed parallel to each other. a flow path decomposition unit; and a network model acquiring unit configured to set each position divided by the flow path decomposition unit as a node and acquire the network model by modeling a section of an adjacent node among the set nodes as a resistance.

Nodes set in the flow channel of the network model acquisition unit may be connected by resistance according to a pattern in which the flow channel is formed.

Nodes set in the network model acquisition unit may be connected to adjacent nodes among nodes set in the porous electrode through resistance.

The network analyzer calculates the flow rate change of the closed loop in the network model so that the mass conservation law and the energy conservation law are satisfied in each of the plurality of closed loops.

(where j is the closed loop identifier, i is the resistance identifier in the closed loop, Q is the flow rate, ΔQ is the change in flow rate due to the resistance of the closed loop, θ is the flow direction (clockwise is 1, counterclockwise is -1), ΔP is the pressure drop due to the resistance of the closed loop, and n represents the number of iterations).

The network analysis unit channel pressure drop due to resistance connected between nodes in the flow channel (ΔP _ch ) and electrode pressure drop due to resistance connected between nodes in the porous electrode (ΔP _p ) and nodes of the flow channel The internal pressure drop (ΔP _inter ) due to the resistance connected between the nodes of the corresponding porous electrode can be separately calculated.

A flow battery simulation method according to another embodiment of the present invention for achieving the above object is implemented as a porous electrode in a flow battery and a predetermined pattern on one surface of the porous electrode to supply an applied electrolyte to the porous electrode. The flow path structure of the flow path formed by the channel is confirmed, and according to the identified flow path structure, the porous electrode and the flow channel are divided based on a plurality of nodes having predetermined distance intervals, and the divided Generating a network model of a structure in which adjacent nodes among a plurality of nodes are connected with resistance that hinders electrolyte flow; and a flow rate flowing in and out of each of a plurality of nodes of the network model satisfies the law of conservation of mass, and a pressure drop in a closed loop composed of resistors connecting adjacent nodes among the plurality of nodes satisfies the law of conservation of energy. , calculating the flow rate and pressure drop between each node of the network model and analyzing the network model.

Therefore, the flow cell simulation apparatus and method according to an embodiment of the present invention creates a fluid dynamics network model with a simple structure by modeling each configuration on the flow path through which liquid or gaseous electrolyte flows in the flow cell as a flow resistance element, , the flow state can be quickly analyzed at low computational cost based on the generated fluid dynamics network model. Therefore, since a high-performance computing device is not required, it can be implemented at low cost in an existing general battery management system.

1 shows an example of a flow battery configuration.
Figure 2 shows an example of a battery cell structure classified according to the way the flow flows into the porous electrode.
3 shows an example of a flow channel structure of a flow battery.
FIG. 4 shows a flow transmission path according to the flow channel structure of FIG. 3 .
5 is a diagram for explaining the flow battery simulation concept of the present invention.
6 shows a method of generating a multi-layer fluid dynamics network model according to the present embodiment.
FIG. 7 is a diagram for explaining node positions set for flow analysis of the multilayer fluid dynamics network model of FIG. 6 .
8 shows an example of the generated multilayer fluid dynamics network model.
9 shows a schematic configuration of a flow battery simulation device according to an embodiment of the present invention.
10 to 12 show the analysis performance of the flow battery simulation device according to the present invention.
13 shows a flow battery simulation method according to an embodiment of the present invention.

In order to fully understand the present invention and its operational advantages and objectives achieved by the practice of the present invention, reference should be made to the accompanying drawings illustrating preferred embodiments of the present invention and the contents described in the accompanying drawings.

Hereinafter, the present invention will be described in detail by describing preferred embodiments of the present invention with reference to the accompanying drawings. However, the present invention may be embodied in many different forms and is not limited to the described embodiments. And, in order to clearly describe the present invention, parts irrelevant to the description are omitted, and the same reference numerals in the drawings indicate the same members.

Throughout the specification, when a part "includes" a certain component, it means that it may further include other components, not excluding other components unless otherwise stated. In addition, terms such as "... unit", "... unit", "module", and "block" described in the specification mean a unit that processes at least one function or operation, which is hardware, software, or hardware. And it can be implemented as a combination of software.

1 shows an example of a flow battery configuration, and FIG. 2 shows an example of a battery cell structure classified according to a method in which flow flows into a porous electrode.

1 shows a schematic structure of a vanadium redox flow battery as an example of a flow battery. Referring to FIG. 1, the flow battery includes two tanks 111 and 112 in which anolyte, which is a positive electrolyte, and catholyte, which is a negative electrolyte, are respectively stored, and the anolyte and negative electrode from the two tanks, respectively. A stack 120 in which liquid flows in and generates a chemical reaction to obtain power, and anolyte and catholyte stored in the corresponding tank among the two tanks 111 and 112 are circulated through the stack 120 during charging or discharging. It may include two pumps 113 and 114 and a load/power unit 130 that uses power generated in the stack 120 during discharging or supplies power to the stack 120 during charging to charge it.

The stack 120 includes an ion exchange membrane (or ion selective membrane) 121 having selective permeability and two porous electrodes 122 and 123 positioned on both sides with the ion exchange membrane 121 interposed therebetween. ) and first and second electrodes 124 and 125 for collecting electric charges generated in the stack 120 and supplying them to the load/power supply unit 130 . Here, the two porous electrodes 122 and 123 are reaction electrodes that cause oxidation/reduction reactions with the anolyte and catholyte. Since oxidation/reduction reactions occur at the interface of the electrodes, a porous electrode is used to increase the reaction area. is implemented as Here, the anolyte and catholyte react with the porous electrodes 122 and 123 while circulating between the stack 120 and the two tanks 111 and 112 by pumps 113 and 114 . That is, the anolyte and catholyte are introduced into one end of the stack 120 and discharged through the other end.

Here, although the stack 120 implemented with one battery cell is shown as an example, the stack 120 may be configured to include a plurality of battery cells.

Referring to FIG. 2 , (a) shows a conventional battery cell structure in which positive and negative electrolytes are circulated through the entire porous electrode, and (b) shows a battery cell structure in which a flow channel is formed.

In the conventional battery cell structure shown in (a), since the electrolyte can be circulated only through the entire porous electrode, the supply of electrolyte for each position of the porous electrodes 122 and 123 is non-uniform according to the circulation direction, and the pressure drop is too There is a big problem that arises. In addition, since the thickness of the porous electrodes 122 and 123 must be thick, there is a problem in that ohmic resistance increases.

In contrast, in the battery cell of (b), flow channels 126 and 127 through which electrolyte can easily flow are formed along one side of the porous electrodes 122 and 123 . In the battery cell structure shown in (b), the active material flows along one side of the porous electrodes 122 and 123 and flows into the porous electrodes 122 and 123 to cause a reaction. Accordingly, the electrolyte can be uniformly supplied to the porous electrodes 122 and 123 and a large pressure drop is not generated. Here, the flow channels 126 and 127 are formed by being etched according to a predetermined pattern on a bipolar plate 230 positioned between one side of the porous electrode and the first and second electrodes 124 and 125. It can be.

3 shows an example of a flow channel structure of a flow battery, and FIG. 4 shows a flow transmission path according to the flow channel structure of FIG. 3 .

In FIG. 3, (a) shows a case where a serpentine flow channel 210 is formed, and (b) shows a case where interdigitated flow channels 221 and 222 are formed. And Figure 4 (a) shows the path through which the flow applied to the inlet of the serpentine flow channel 210 flows through the porous electrode 122 while being discharged to the outlet, (b) is the flow channel 221 and 222 show the path through which the flow applied to the inlet of the first flow channel 221 flows through the porous electrode 122 while being discharged to the outlet of the second flow channel 222. . Here, for convenience of description, only the porous electrode 122 and the flow channels 210, 221, and 222 located on one side of the ion exchange membrane 121 are shown, but the same applies to the porous electrode 123 located on the other side. Flow channels 210, 221 and 222 are formed.

As shown in (a) of FIG. 3, the serpentine flow channel 210 is formed in a zigzag pattern in which a single channel is repeatedly bent on one surface of the porous electrode 122, and therefore, certain regions of the channel are positioned parallel to each other. do. Then, the flow applied to the inlet of the serpentine flow channel 210 formed on one surface of the porous electrode 122 flows to the outlet along the formed channel pattern and is discharged. At this time, as shown in (a) of FIG. 4, the flow introduced into the serpentine flow channel 210 not only flows along the channel pattern, but also the porous electrode in the rib section between channel regions located adjacent to each other. It flows through and can be delivered to other areas on the flow channel.

And as shown in (b) of FIG. 3, the interdigitated flow channel is formed in a pattern in which two flow channels 221 and 222 having a comb-shaped pattern are interdigitated with each other, so that the two flow channels ( 221, 222) is composed of a pattern in which comb teeth are positioned alternately with each other in the comb shape. Here, an inlet is formed in the first flow channel 221 to allow flow to flow in, and an outlet is formed in the second flow channel 222 . Therefore, as shown in (b) of FIG. 4 , the flow supplied to the first flow channel 221 is supplied to the second flow channel 222 through the porous electrode 122 and discharged again.

Therefore, in the serpentine flow channel 210, while the flow flows from the inlet to the outlet of the flow channel 210 along the channel, it flows into the porous electrode 122, so some of the flow flows into the porous electrode 122, whereas the interdigitated flow channel In (221, 222), since the first flow channel 221 with the inlet and the second flow channel 222 with the outlet have a separate structure, the flow passes through the porous electrode 122 to the first flow channel 221. ) to the second flow channel 222 has a structure.

5 is a diagram for explaining the flow battery simulation concept of the present invention.

FIG. 5 shows a simulation technique for flow analysis in the case where a serpentine flow channel 210 is formed on the porous electrode 122 shown in FIG. 3 (a). In FIG. 5, (a) and (b) show an example of a flow analysis method in the existing CFD simulation technique, and (c) and (d) show an example of a flow analysis method in the simulation technique according to the present embodiment. indicate

As shown in (a) and (b), in the conventional CFD simulation technique, according to the structure of the flow channel 210 and the porous electrode 122, a number of numbers (for example, 10 10,000 or more) grids are set and the flow state is calculated in each of the set grids, so the calculation cost is very high.

In contrast, in this embodiment, as shown in (c) and (d), each of the flow channel 210 and the porous electrode 122, which are structures on the flow path, are modeled as resistance, which is an obstacle to flow, to obtain a multilayer fluid dynamics network. Create and analyze models. That is, the flow channel 210 and the porous electrode 122, which have physically different flow characteristics, are divided into different layers, and each layer is divided into a plurality of regions according to locations designated as nodes (nd), Flow state analysis is performed by modeling each separated region as a resistance connected between adjacent nodes (nd). Therefore, in the simulation technique according to the present embodiment, the number of nodes is reduced to 1/1000 level compared to the number of grids of the existing simulation technique shown in (a) and (b), so that the amount of calculation can be greatly reduced.

FIG. 6 shows a method of generating a multilayer fluid dynamics network model according to the present embodiment, and FIG. 7 is a diagram for explaining node locations set for flow analysis of the multilayer fluid dynamics network model of FIG. 6 .

Referring to (a) and (b) of FIG. 6 , in order to generate a multilayer fluid dynamics network model according to the present embodiment, first, a channel layer in which the flow channel 210 is located and an electrode layer in which the porous electrode 122 is located distinguish This is because flow characteristics in the flow channel 210 and the porous electrode 122 are very different from each other. The separated channel layer and the electrode layer can be seen as being spaced apart by an internal length (L _inter ) based on the center of the channel layer and the center of the electrode layer. That is, the inner length (L _inter ) represents the distance between the center of the channel layer and the center of the electrode layer.

In the channel layer, the flow channel is divided into a plurality of regions according to the pattern formed thereon. In this case, the channel layer may be classified based on a bending position or branching position of the flow channel 210 formed in a predetermined pattern. As shown in FIGS. 3 and 4, the flow channels 210, 221, and 222 formed in a predetermined pattern may be bent in a “c” shape or a “c” shape or branched in a “TT” shape. Due to this, some sections of the flow channels 210, 221, and 222 may be disposed adjacent to each other and parallel to each other. That is, the flow channels 210, 221, and 222 may be divided into a plurality of relatively long-length sections and short-length sections centered on a plurality of bending positions or branching positions.

Further, the divided long sections of the flow channels 210, 221, and 222 may be divided into predetermined unit lengths. Here, the unit length dividing the long interval is referred to as a channel length (L _ch ), and the channel length (L _ch ) may be pre-specified by a user.

On the other hand, the electrode layer is preset based on the channel length (L _ch ) and the distance between the centers of the channel regions adjacent to each other in the channel region disposed in parallel by the bent pattern flow channels 210, 221, and 222. Areas may be divided according to the length (L _p ). For example, as shown in (a) of FIG. 3 , since the adjacent channel regions of the serpentine flow channel 210 constitute the same flow channel, the electrode length L _p may correspond to a short section of the bent flow channel. On the other hand, in the interdigitated flow channels 221 and 222 in which the two flow channels 221 and 222 are interdigitated, the electrode length L _p is different from each other because the adjacent channel area is the area of the relative flow channel. , 222) may correspond to the spacing between adjacent channel regions.

At this time, for ease of calculation later, it is preferable to set the _channel length (L ch ) such that the long section of the flow channels (210, 221, 222) is an integer multiple of the channel length (L _ch ), similarly between adjacent channel regions It is desirable that the electrode length (L _p ) be set so that the interval of the electrode length (L _p ) is an integer multiple, but is not limited thereto.

FIG. 6 illustrates, for example, a case in which the distance between adjacent channel regions is set to be twice the length of the electrode (L _p ), that is, the distance between the electrode lengths (L _p ) is 1/2 of the distance between the adjacent channel regions.

As described above, when each area of the channel layer and the electrode layer is divided, each position divided by the channel length (L _ch ) and the electrode length (L _p ) from the center of the channel layer and the center of the electrode layer is set as a node (nd), , the region between each node nd can be modeled as a resistance component that obstructs the flow. In the present invention, a node (nd) is set by replacing the existing grid, and a flow state is calculated based on the set node (nd).

In FIGS. 6 and 7, Q _ch , Q _p, and Q _inter represent the flow rates of each modeled zone divided into nodes, and t _f and t _p are flow channels 210, 211, and 212, which are channel layers, and electrode layers, respectively. Denotes the thickness of the porous electrodes 122 and 123, W _ch and W _r denote the width of the flow channels 210, 211 and 212 and the rib spacing between adjacent channel regions, respectively. Here, the electrode length (L _p ) represents a distance divided and set based on the center of the adjacent channel region, while W _r represents the distance between adjacent sides of the adjacent channel region. However, since the width of the flow channels 210, 211, and 212 is W _ch , the distance from the node nd located at the center of the flow channel to the side of the channel should be W _ch /2, but in the present invention, considering the flow characteristics Therefore, the distance from the node nd to the side of the flow channel is defined as W _ch /4 regardless of the physical width (W _ch ) of the flow channel.

As shown in (a) and (b) of FIG. 5 , in the existing simulation technique, a lot of grids are set with a density proportional to the flow state change for flow analysis, and the flow state in each grid is analyzed. However, since the flow state analysis is actually used to control the circulation amount of the electrolyte for the operation of the flow battery, analyzing the flow state at all positions of the flow channels 210, 211, and 212 and the porous electrodes 122 and 123 is Very inefficient. Accordingly, in the present invention, as shown in FIG. 7, the input and output of the flow and the flow of the flow are interrupted around the node (nd) set at predetermined intervals in consideration of the flow transfer path for the flow having different states for each location. The calculation of the flow analysis is simplified by modeling the fluid dynamics network model composed of the resistance to analyze the flow rate and pressure drop at each node (nd).

At this time, it is assumed that the flow of electrolyte ideally moves only between nodes, and it is analyzed by assuming that it is laminar flow, incompressible flow, and steady state flow.

8 shows an example of the generated multilayer fluid dynamics network model.

In FIG. 8, (a) shows a network model for the electrode layer, (b) shows a network model for the channel region, and (c) is for explaining the flow analysis at a specific node (nd) of the multilayer fluid dynamics network model. it is a drawing

Referring to FIGS. 6 to 8 , first, the internal length (L _inter ) and the electrode length (L _p ) may be calculated according to Equations 1 and 2, respectively.

Here, the electrode length (L _p ) set to be 1/2 of the interval between adjacent channel regions is calculated as in Equation 2 instead of (W _ch + W _r )/2, as described above, from the node (nd) This is because the distance to the side of the channel is defined as W _ch /4.

And, the channel length (L _ch ) is pre-specified by the user as a predetermined unit channel length.

The channel pressure drop (ΔP _ch ) of the flow occurring in the flow channels (210, 211, 212) is the frictional loss (ΔP _f ) caused by friction and the bending of the flow channels (210, 211, 212), etc. Since it is determined by the minor loss (ΔP _minor ) factor due to the structure of Equation 3, it can be calculated.

Here, ΔP _f represents the pressure drop due to friction loss, and ΔP _minor represents the pressure drop due to negative loss.

In Equation 3, the pressure drop due to friction loss (ΔP _f ) can be calculated by Equation 4 according to the Darcy-Weisbach equation.

where ρ is the electrolyte density, f is the Fanning friction factor, Q _f is the flow rate in the channel area, L _ch , A _ch and D _h,ch are the unit channel length, channel cross-section area and flow channel, respectively. means the hydraulic diameter of the flow channel.

And the hydraulic diameter (D _h,ch ) is calculated according to Equation 5, and the panning friction coefficient (f) is calculated according to Equation 6.

Here, a is the aspect ratio of the channel width and depth, and Re is the Reynolds number.

Meanwhile, the pressure drop due to negative loss is calculated by Equation 7 according to the bending structure of the flow channel.

Here, K _b is a bend loss and may be determined as shown in Equation 8 by the Reynolds number (Re).

Here, L _s represents the spacer length.

Meanwhile, the electrode pressure drop due to the porous electrode in the electrode layer (ΔP _p ) is calculated by Equation 9 according to Darcy's law corrected by Forchheimer.

where μ is the viscosity of the electrolyte, κ is the permeability of the porous electrode, Q _p and A _p represent the flow rate and cross-sectional area in the porous electrode, respectively, and β represents the Polchheimer coefficient.

The Folchheimer coefficient (β) of Equation 9 can be obtained according to Equation 10.

Here, ε represents the porosity of the porous electrode.

In addition, the internal pressure drop (ΔP _inter ) occurring in the region between the channel layer and the electrode layer is calculated by Equation 11 as a major loss for the corresponding length because the flow flows through both the flow channel and the porous electrode.

And referring to (c) of FIG. 8, in the generated network model, each node (nd) has an inflow flow rate (Q' _p , Q" _p ) and an outflow flow rate (Q _inter , Q _p , Q"' _p ) The mass conservation equation according to Equation 12 must be satisfied.

In (c) of FIG. 8, nodes located in the electrode layer are shown, but nodes located in the channel layer must also satisfy the mass conservation equation.

Meanwhile, as shown in (a) and (b) of FIG. 8 , each closed loop formed by connecting four nodes in the generated network model must satisfy the energy conservation equation of Equation 14.

Here, θ is the flow direction (clockwise is 1, counterclockwise is -1), j is the closed loop identifier, and i represents the resistance identifier in the closed loop.

Since the generated multilayer fluid dynamics network model is a set of a plurality of closed loops composed of a plurality of nodes, all nodes and all closed loops in the network model must satisfy the conservation of mass equation of Equation 13 and the conservation of energy equation of Equation 14. do. Therefore, iterative calculation is performed as shown in Equation 15 using the Hardy-Cross technique to satisfy the conservation of mass equation and the conservation of energy equation at each node and each closed loop.

Here, ΔQ _j represents the flow rate change in the j-th loop, and n represents the number of iterations.

9 shows a schematic configuration of a flow battery simulation device according to an embodiment of the present invention.

Referring to FIG. 9 , the flow battery simulation device according to the present embodiment may include a network model generation unit 310 and a network analysis unit 320. The network model generation unit 310 generates a multi-layer fluid dynamics network model according to a predetermined method from a flow path structure along a flow path through which electrolyte is delivered in a flow battery. The network model generator 310 may include a flow path structure acquisition unit 311 , a flow path decomposition unit 312 and a network model acquisition unit 313 .

The flow path structure acquisition unit 311 acquires a flow path structure along a flow path through which an electrolyte (or active material) is delivered in a flow battery to be analyzed. Here, the flow path structure includes the size of the porous electrodes 122 and 123 and the types and formation patterns of the flow channels 210, 212 and 222.

When the flow path structure is confirmed by the flow path structure acquisition unit 311, the flow path decomposition unit 312 confirms the structures of the porous electrodes 122 and 123 and the flow channels 210, 212 and 222 from the identified flow path structure, and Disassemble in the specified way. In particular, the flow channels 210, 212, and 222 and the porous electrodes 122 and 123 may be divided into a plurality of regions according to the patterns in which the flow channels 210, 212, and 222 are formed.

Here, as shown in FIG. 3, the flow channels 210, 212, and 222 are formed by closely contacting one surface of the porous electrodes 122 and 123 in the battery cell of the stack, so that the electrolyte flows through the flow channels 210, 212, and 222. It is assumed to pass through the porous electrodes 122 and 123. Accordingly, the flow path disassembly unit 312 disassembles the flow channels 210, 212, and 222 and the porous electrodes 122 and 123 in the battery cell. The flow path decomposition unit 312 first decomposes the flow channels 210, 212, and 222 based on the bending position of the formed pattern, and divides a long section in the decomposed pattern according to a predetermined channel length (L _ch ). . And the porous electrodes (122, 123) along with the channel length (L _ch ) in the decomposed pattern of the flow channel (210, 212, 222) a number of according to the electrode length (L _p ) specified based on the length of the short section divided into rectangular areas. Here, the electrode length (L _p ) can be obtained as in Equation 2 regardless of the cross-sectional structure of the actual flow channels 210, 212, and 222.

When the flow channels 210, 212, and 222 and the porous electrodes 122 and 123 of the flow path are disassembled by the flow path decomposition unit 312, the flow channels 210, 212, and 222 and the porous electrodes 122 and 123 Each decomposed position is set as a node (nd), and a plurality of set nodes (nd) are set to be connected by resistance that hinders the flow in the corresponding area to create a network model. At this time, the nodes set in the flow channels 210, 212, and 222 are connected with resistance according to the pattern in which the flow channels are formed, as shown in (c) and (d) of FIG. 5, and the porous electrodes 122 and 123 Nodes set in are connected to adjacent nodes by resistance.

In addition, regions between a plurality of nodes nd set in the flow channels 210, 212, and 222 and corresponding nodes nd set in the porous electrodes 122 and 123 are also set to be connected by internal resistance.

Here, the network model can be viewed as a fluid dynamics network model for analyzing the fluid dynamics of the flow path in the stack. Since it is created to be divided into different layers, it can be called a multi-layer fluid dynamics network model.

Based on the multilayer fluid dynamics network model obtained by the network model generation unit 310, the network analyzer 320 satisfies the mass conservation law based on the flow rate of each of the plurality of nodes, and each of the plurality of closed loops is dependent on the pressure drop. The flow rate and pressure of the electrolyte are analyzed for each region divided on the flow path by iteratively calculating to satisfy the energy conservation law.

That is, the network analyzer 320 requires that the flow rate flowing into and out of each node in the obtained multilayer fluid dynamics network model satisfy the mass conservation equation as shown in Equation 13, and is formed as a resistance connecting between four adjacent nodes. Based on the fact that the pressure drop must satisfy the energy conservation equation as shown in Equation 14 in each of the plurality of closed loops that are do.

Here, the iterative calculation is performed by converting the flow rate and pressure of the previously calculated closed loop to the flow rate and pressure of the adjacent closed loop until all nodes of the obtained multilayer fluid dynamics network model satisfy the conservation equation of mass and all closed loops satisfy the conservation equation of energy. And it can be performed in a way of updating to reflect in the calculation.

10 to 12 show the analysis performance of the flow battery simulation device according to the present invention.

10 and 11 show analysis results for the internal pressure and internal flow velocity in the case where a serpentine flow channel and an interdigitated flow channel are formed, respectively. , and (b) shows the result of analyzing the flow rate for each location. In addition, in (a) and (b) of FIGS. 10 and 11, the left side shows the analysis result obtained according to the existing grid-based simulation technique (here, COMSOL as an example), and the right side shows the node-based simulation technique according to this embodiment. The analysis results obtained according to the following are shown. And FIG. 12 shows the result of calculating the pressure drop according to the input flow rate when the serpentine flow channel and the interdigitated flow channel are formed.

Meanwhile, Table 1 shows the result of calculating the average flow velocity of the electrolyte transported along the inside of the flow path according to the conventional grid-based simulation technique (COMSOL) and the node-based simulation technique according to the present embodiment.

As shown in FIGS. 10 to 12 and Table 1, the simulation device according to the present embodiment uses an infinite number of grids (typically 100,000 units) compared to conventional simulation techniques that must be calculated at high computational cost, As it uses a very small number of nodes (in units of 100), it can be seen that it has a low calculation error (approximately 10%) even though the calculation is performed at a low calculation cost. This error is actually an error due to the fact that the multilayer fluid dynamics network model of this embodiment is set based on a small number of nodes and calculated as the average value for each region, and is negligible when analyzing the overall flow state in the stack. .

13 shows a flow battery simulation method according to an embodiment of the present invention.

Referring to FIG. 13, in the flow battery according to the present embodiment, a network model generation step (S10) of generating a multilayer fluid dynamics network model from a flow path structure along a flow path through which electrolyte is delivered, and based on the generated multilayer fluid dynamics network model It can be composed of a network model analysis step (S20) of analyzing the flow state on the flow path.

In the network model generation step (S10), first, a flow path structure according to a flow path through which an electrolyte (or active material) is delivered in a flow battery to be analyzed is obtained (S11). When the channel structure is confirmed, the channel layer corresponding to the flow channels 210, 212, and 222 having different flow characteristics and the electrode layer corresponding to the porous electrodes 122 and 123 are separated (S12). Then, each of the separated channel layer and the electrode layer is divided in a predetermined manner (S13). At this time, in the channel layer, the flow channels 210, 212, and 222 may be decomposed based on the bending position of the formed pattern, and a long section in the decomposed pattern may be divided again according to a predetermined channel length (L _ch ). And in the electrode layer, the porous electrodes 122 and 123 are channel lengths (L _ch ) along with the electrode lengths (L _p ) specified based on the lengths of the short sections in the decomposed patterns of the flow channels (210, 212, 222). It can be divided into a number of rectangular areas.

When the regions of the channel layer and the electrode layer are separated, each decomposed position in the flow channels 210, 212, 222 and the porous electrodes 122, 123 is set as a node (nd) (S14). Then, nodes adjacent to each other among the set nodes nd are connected with a resistance that hinders the flow to create a multi-layer fluid dynamics network model (S15).

When the multilayer fluid dynamics network model is created, in the network model analysis step (S20), the flow rate for each location is calculated centering on each node of the generated network model (S21). Then, based on the calculated flow rate, the pressure drop for each position is calculated in a plurality of closed loops formed by resistance connecting four adjacent nodes (S22).

Then, it is determined whether the calculated flow rate at each location satisfies the law of conservation of mass and the pressure drop at each location satisfies the law of conservation of energy. If not, the flow rate at each location is repeatedly calculated by reflecting the calculated pressure drop at each location ( S21). If the calculated flow rate at each location satisfies the law of conservation of mass and the pressure drop at each location satisfies the law of conservation of energy, the calculation is terminated since both the pressure and flow rate at each location of each network model have been analyzed (S24).

In the above, for convenience of explanation, the case where the stack includes one battery cell is assumed, but when the stack includes a plurality of battery cells, the simulation apparatus and method classify each battery cell and model a multi-layer fluid dynamics network. It can be configured to generate and interpret the generated multi-layer fluid dynamics network model.

The method according to the present invention may be implemented as a computer program stored in a medium for execution on a computer. Here, computer readable media may be any available media that can be accessed by a computer, and may also include all computer storage media. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, including read-only memory (ROM) dedicated memory), random access memory (RAM), compact disk (CD)-ROM, digital video disk (DVD)-ROM, magnetic tape, floppy disk, optical data storage device, and the like.

Although the present invention has been described with reference to the embodiments shown in the drawings, this is only exemplary, and those skilled in the art will understand that various modifications and equivalent other embodiments are possible therefrom.

Therefore, the true technical protection scope of the present invention should be determined by the technical spirit of the appended claims.

111, 112: electrolyte tank 113, 114: pump
121: ion exchange membrane 122, 123: porous electrode
124, 125: first and second electrodes 130: load/power unit
126, 127: flow channel 210: serpentine flow channel
221, 222: Interpod type flow channel 310: Network model generation unit
311: flow path structure acquisition unit 312: flow path decomposition unit
313: network model acquisition unit 320: network analysis unit

Claims (19)

In the flow battery, the flow channel structure of the flow path through which the electrolyte is delivered is formed by a porous electrode and a flow channel implemented in a predetermined pattern on one surface of the porous electrode and supplied to the porous electrode to supply the applied electrolyte to the porous electrode. A network having a structure in which each of the porous electrode and the flow channel is divided based on a plurality of nodes having a predetermined distance interval according to the structure of the flow path, and adjacent nodes among the plurality of divided nodes are connected by resistance to hinder electrolyte flow. a network model generating unit generating a model; and
So that the flow rate flowing in and out of each of the plurality of nodes of the network model satisfies the law of conservation of mass, and the pressure drop in a closed loop consisting of resistance connecting adjacent nodes among the plurality of nodes satisfies the law of conservation of energy, Including a network analysis unit for calculating the flow rate and pressure drop between each node of the network model,
The network analyzer
In each of the plurality of closed loops, the change in flow rate of the closed loop in the network model so that the law of conservation of mass and the law of conservation of energy are satisfied by the equation

(where j is the closed loop identifier, i is the resistance identifier in the closed loop, Q is the flow rate, ΔQ is the change in flow rate due to the resistance of the closed loop, θ is the flow direction (clockwise is 1, counterclockwise is -1), ΔP is the pressure drop due to the resistance of the closed loop, and n is the number of iterations.)
Flow cell simulation device that iteratively calculates according to The method of claim 1, wherein the network model generating unit
The flow channel structure of the porous electrode and the flow channel constituting the flow path is checked, and the flow channel is divided into a plurality of sections based on the bending or branching position according to the identified flow channel structure, and the divided sections are arranged parallel to each other A flow path decomposition unit that divides a plurality of sections into predetermined channel length units and divides the region of the porous electrode according to an electrode length set corresponding to the channel length and a distance between a plurality of sections arranged in parallel with each other. ; and
and a network model acquisition unit configured to set each position divided by the flow path decomposition unit as a node, and acquire the network model by modeling an adjacent node section among the set nodes as a resistance. The method of claim 2, wherein the network model obtaining unit
Nodes set in the flow channel are connected by resistance according to the pattern in which the flow channel is formed. The method of claim 3, wherein the network model obtaining unit
Nodes set in the flow channel are connected to adjacent nodes among the nodes set in the porous electrode by resistance. delete The method of claim 1, wherein the network analyzer
Channel pressure drop due to resistance connected between nodes in the flow channel (ΔP _ch ) and electrode pressure drop due to resistance connected between nodes in the porous electrode (ΔP _p ) and a porous electrode corresponding to the node of the flow channel A flow cell simulation device that separately calculates the internal pressure drop (ΔP _inter ) due to the resistance connected between the nodes of the. The method of claim 6, wherein the network analyzer
The channel pressure drop (ΔP _ch ) is calculated as the sum of the pressure drop (ΔP _f ) due to friction loss and the pressure drop (ΔP minor ) due to _minor losses due to the bending or branching structure of the flow channel,
The pressure drop due to the friction loss (ΔP _f ) is expressed by the equation

(Where ρ is the electrolyte density, f is the panning friction coefficient, Q _f is the flow rate in the channel area, L _ch , A _ch and D _h,ch are the unit channel length, channel cross-sectional area and hydraulic diameter of the flow channel, respectively)
calculated as,
The pressure drop due to the negative loss (ΔP _minor ) is expressed by the equation

(Where K _b is the bending loss determined by the Reynolds number)
A flow cell simulation device calculated as . The method of claim 7, wherein the network analyzer
The electrode pressure drop (ΔP _p ) is calculated by the equation

(Where μ is the viscosity of the electrolyte, κ is the permeability of the porous electrode, Q _p and A _p represent the flow rate and cross-sectional area in the porous electrode, respectively, and β represents the Polchheimer coefficient.)
Flow cell simulation device to calculate according to. The method of claim 8, wherein the network analyzer
The internal pressure drop (ΔP _inter ) is expressed by the equation

Flow cell simulation device to calculate according to. The method of claim 9, wherein the network model obtaining unit
The node is set at the center of the flow channel and the center of the thickness of the porous electrode, and the electrode length (L _p ) is determined according to the flow characteristics of the flow channel by the equation

(Where W _ch is the width of the flow channel, and W _r is the distance between the channel sides facing each other in a plurality of adjacent and parallel sections of the flow channel)
A flow cell simulation device defined as The method of claim 2, wherein the flow path decomposition unit
When the flow channel is a serpentine flow channel, the flow channel is decomposed into a plurality of sections based on the bending position, and a relatively long section among the divided sections is divided into a unit of the channel length. Flow battery simulation device . The method of claim 2, wherein the flow path decomposition unit
If the flow channel is an interdigitated flow channel having two flow channels formed separately from each other in a comb shape, each of the two flow channels is divided into a plurality of sections based on the diverging position, and the relative length of the divided plurality of sections A flow battery simulation device for dividing a long section by the channel length unit. In the flow battery, the flow channel structure of the flow path through which the electrolyte is delivered is formed by a porous electrode and a flow channel implemented in a predetermined pattern on one surface of the porous electrode and supplied to the porous electrode to supply the applied electrolyte to the porous electrode. A network having a structure in which each of the porous electrode and the flow channel is divided based on a plurality of nodes having a predetermined distance interval according to the structure of the flow path, and adjacent nodes among the plurality of divided nodes are connected by resistance to hinder electrolyte flow. creating a model; and
So that the flow rate flowing in and out of each of the plurality of nodes of the network model satisfies the law of conservation of mass, and the pressure drop in a closed loop consisting of resistance connecting adjacent nodes among the plurality of nodes satisfies the law of conservation of energy, Analyzing the network model by calculating the flow rate and pressure drop between each node of the network model,
Analyzing the network model
The flow rate change of the closed loop in the network model so that the mass conservation law and the energy conservation law are satisfied in each of the plurality of closed loops

(where j is the closed loop identifier, i is the resistance identifier in the closed loop, Q is the flow rate, ΔQ is the change in flow rate due to the resistance of the closed loop, θ is the flow direction (clockwise is 1, counterclockwise is -1), ΔP is the pressure drop due to the resistance of the closed loop, and n is the number of iterations.)
Flow cell simulation method that iteratively calculates according to.
14. The method of claim 13, wherein generating the network model
The flow channel structure of the porous electrode and the flow channel constituting the flow path is confirmed, and the flow channel is divided into a plurality of sections based on the bending or branching position according to the identified flow channel structure, and the divided sections are arranged parallel to each other Dividing a plurality of sections by predetermined channel length units, and dividing regions of the porous electrode according to an electrode length set corresponding to the channel length and a distance between a plurality of sections disposed parallel to each other; and
A flow battery simulation method comprising the step of setting each of the positions distinguished from the flow path as a node and modeling an adjacent node section among the set nodes as a resistance to obtain the network model. 15. The method of claim 14, wherein obtaining the network model comprises:
A flow battery simulation method for connecting nodes set in the flow channel with resistance according to a pattern in which the flow channel is formed. 16. The method of claim 15, wherein obtaining the network model comprises:
A flow battery simulation method for connecting nodes set in the flow channel with adjacent nodes among nodes set in the porous electrode by resistance. delete 14. The method of claim 13, wherein interpreting the network model comprises:
Channel pressure drop due to resistance connected between nodes in the flow channel (ΔP _ch ) and electrode pressure drop due to resistance connected between nodes in the porous electrode (ΔP _p ) and a porous electrode corresponding to the node of the flow channel A flow cell simulation method that separately calculates the internal pressure drop (ΔP _inter ) due to the resistance connected between the nodes of the. 19. The method of claim 18, wherein obtaining the network model comprises:
Set the node at the center of the flow channel and the center of the thickness of the porous electrode, and the electrode length (L _p ) is determined according to the flow characteristics of the flow channel by the equation

(Where W _ch is the width of the flow channel, and W _r is the distance between the channel sides facing each other in a plurality of adjacent and parallel sections of the flow channel)
A flow cell simulation method defined as

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