A fuel cell diffusion layer optimization method based on encapsulation mechanics
Patent Information
- Application Number
- CN202310743311.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2023-06-21
- Publication Date
- 2026-10-16
- Estimated Expiration
- 2043-06-21
AI Technical Summary
但由于氢在特定浓度下与空气易燃易爆的特性，因此要极为注意燃料电池对于电池密封及封装这一问题
[0027] The beneficial effects of this invention are as follows: By optimizing the thickness of the diffusion layer in a three-dimensional proton exchange membrane fuel cell, and under the premise of a determined encapsulation pressure, this invention ensures that the diffusion layer achieves a uniform thickness after being subjected to pressure, thus minimizing the impact of encapsulation pressure on the stack reaction. Furthermore, modeling and simulation of the optimized fuel cell confirms the achievement of the optimization effect.
Smart Images
Figure CN116822187B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of fuel cells, and specifically to an optimization and detection method for the diffusion layer of a three-dimensional proton exchange membrane fuel cell based on encapsulation mechanics. Background Technology
[0002] Proton exchange membrane fuel cells (PEMFCs) are considered one of the most promising new energy sources of the 21st century due to their advantages, including no Carnot cycle limitations, high energy conversion efficiency, low operating temperature, high power density, and being green and pollution-free. However, because hydrogen is flammable and explosive with air at certain concentrations, extreme care must be taken regarding the sealing and encapsulation of the fuel cell.
[0003] Under normal circumstances, fuel cells rely on endplates on both sides to apply reliable sealing pressure. Sufficient sealing pressure is needed to ensure an absolute seal, while excessive sealing pressure must be avoided to prevent deformation and damage to internal components. Given this, and considering the already determined sealing pressure of the endplates, the diffusion layer, which is subject to greater deformation, becomes the best target for optimization. Summary of the Invention
[0004] To address the above problems, this invention proposes a method for optimizing and detecting the diffusion layer of a fuel cell based on encapsulation mechanics. This method optimizes the bipolar plate of a fuel cell with a fixed encapsulation pressure, thereby improving the deformation of the fuel cell diffusion layer, increasing the fuel transport channels, and promoting the distribution of water, oxygen, and hydrogen.
[0005] The technical solution of the present invention includes the following steps:
[0006] Step 1: Establish a three-dimensional geometric model of a proton exchange membrane fuel cell:
[0007] A three-dimensional geometric model of a proton exchange membrane fuel cell was established, which includes bipolar plates, a diffusion layer, a catalyst layer, and a proton exchange membrane.
[0008] Step 2: Mesh the three-dimensional proton exchange membrane fuel cell geometric model:
[0009] The geometric model of the three-dimensional proton exchange membrane fuel cell established in step 1 is meshed, specifically including the bipolar plate, diffusion layer, catalyst layer, and proton exchange membrane interior are meshed in 3D, and the boundaries of each part of the fuel cell are meshed in 2D.
[0010] Step 3: Simulate and calculate the geometric model of the three-dimensional proton exchange membrane fuel cell:
[0011] The three-dimensional proton exchange membrane fuel cell geometric model with mesh generation completed in step 2 is simulated and calculated.
[0012] Step 4: Obtain the displacement of the fuel cell diffusion layer.
[0013] Based on the simulation results in step 3, the deformation and displacement of the fuel cell diffusion layer caused by the encapsulation pressure are first obtained, and then the height of the diffusion layer under pressure below the flow channel ridge is obtained.
[0014] Step 5: Adjust the thickness of the fuel cell diffusion layer according to the deformation of the fuel cell diffusion layer caused by the encapsulation pressure: First, subtract the thickness of the diffusion layer after being squeezed below the flow channel ridge due to the encapsulation pressure from the original fuel cell diffusion layer thickness to obtain the height difference Δh.
[0015] Then optimize the thickness of the diffusion layer as follows: change the thickness of the diffusion layer at the contact position with the flow channel ridge to the original thickness plus the height difference Δh, which gives the optimized thickness of the diffusion layer at various points of the fuel cell with unequal thickness.
[0016] Step 6: Detect the optimized displacement of the fuel cell diffusion layer and perform simulation calculations again. Determine whether the displacement of the diffusion layer before and after optimization achieves the desired effect based on the simulation calculations.
[0017] The displacement of the diffusion layer in the optimized proton exchange membrane fuel cell was detected to determine whether the diffusion layer of the optimized fuel cell could achieve a consistent thickness after being subjected to encapsulation pressure.
[0018] Step 7: If the goal of uniform thickness of the diffusion layer after pressure is not achieved, repeat the steps until the goal is achieved.
[0019] Furthermore, the bipolar plate flow channel of the three-dimensional proton exchange membrane fuel cell in step 1 can be a serpentine flow channel, a parallel flow channel, an interdigitated flow channel, a spiral flow channel, a grid flow channel, or a biomimetic flow channel, etc.
[0020] Furthermore, in step 1, the bipolar plate flow channels of the three-dimensional proton exchange membrane fuel cell may have different degrees of overlap, that is, the ridges and flow channels of the anode and cathode are not completely symmetrical.
[0021] Furthermore, the dimensional data of each part of the three-dimensional proton exchange membrane fuel cell geometric model in step 1 are not unique and can be changed according to the actual situation.
[0022] Furthermore, in step 3, the three-dimensional proton exchange membrane fuel cell geometric model with mesh generation completed in step 2 is simulated and calculated. Specifically, this includes changing the material properties of the bipolar plate, diffusion layer, catalyst layer, and proton exchange membrane; adding boundary conditions, setting uniformly distributed assembly pressure on the upper and lower surfaces of the bipolar plate, assuming symmetrical boundary conditions on the left and right surfaces of the computational domain, and setting other surfaces as free surfaces; adding computational variables, and setting the deformation of the diffusion layer to view the results.
[0023] Furthermore, step 4 obtains the displacement of the fuel cell diffusion layer, including the diffusion layer displacement cloud map and displacement data.
[0024] Furthermore, the height increased below the flow channel ridge of the fuel cell diffusion layer in step 5 is determined based on the original height of the diffusion layer that was pressed down by the flow channel ridge.
[0025] Furthermore, the optimized fuel cell diffusion layer obtained in step 5 is a diffusion layer of unequal thickness, with a corrugated upper surface, meaning that the diffusion layer below the flow channel is thinner, and the diffusion layer below the flow channel ridge is thicker.
[0026] Furthermore, in step 6, the only difference between the fuel cells before and after optimization, in terms of simulation conditions such as geometric parameters, boundary conditions, initialization conditions, and number of iterations, is the thickness of the fuel cell diffusion layer.
[0027] The beneficial effects of this invention are as follows: By optimizing the thickness of the diffusion layer in a three-dimensional proton exchange membrane fuel cell, and under the premise of a determined encapsulation pressure, this invention ensures that the diffusion layer achieves a uniform thickness after being subjected to pressure, thus minimizing the impact of encapsulation pressure on the stack reaction. Furthermore, modeling and simulation of the optimized fuel cell confirms the achievement of the optimization effect. Attached Figure Description
[0028] Figure 1 This is the workflow diagram for this case;
[0029] Figure 2 It is a three-dimensional geometric model of a proton exchange membrane fuel cell.
[0030] Among them, 1. Bipolar plate anode; 2. Bipolar plate cathode; 3. Diffusion layer; 4. Catalytic layer; 5. Proton exchange membrane.
[0031] Figure 3 This diagram illustrates how the thickness of the fuel cell diffusion layer is adjusted based on the deformation caused by the encapsulation pressure. Detailed Implementation
[0032] To clearly illustrate the technical features of this patent, the following detailed description is provided through specific embodiments and in conjunction with the accompanying drawings.
[0033] In this embodiment, a method for optimizing and verifying the diffusion layer of a three-dimensional proton exchange membrane fuel cell based on encapsulation mechanics is first provided; (Refer to...) Figure 1 As shown, the optimization and testing method for the diffusion layer of a three-dimensional proton exchange membrane fuel cell based on encapsulation mechanics can include the following steps:
[0034] Step 1: Establish a three-dimensional geometric model of a proton exchange membrane fuel cell;
[0035] Establish a three-dimensional geometric model of a proton exchange membrane fuel cell, such as Figure 2As shown, the model includes a bipolar anode 1, a bipolar cathode 5, a diffusion layer 2, a catalyst layer 3, and a proton exchange membrane 4;
[0036] Step 2: Mesh the three-dimensional proton exchange membrane fuel cell geometric model;
[0037] The geometric model of the three-dimensional proton exchange membrane fuel cell established in step 1 is meshed, specifically including dividing the bipolar plate, diffusion layer 2, catalyst layer 3, and proton exchange membrane 4 into 3D meshes, and dividing the boundaries of each part of the fuel cell into 2D meshes.
[0038] Step 3: Perform simulation calculations on the three-dimensional proton exchange membrane fuel cell geometric model;
[0039] The three-dimensional proton exchange membrane fuel cell geometric model with mesh generation completed in step 2 is simulated and calculated. Specifically, the material properties of the bipolar plate, diffusion layer, catalyst layer, and proton exchange membrane are changed; boundary conditions are added, the assembly pressure is set to be uniformly distributed on the upper and lower surfaces of the bipolar plate, the left and right surfaces of the computational domain are assumed to be symmetrical boundary conditions, and the other surfaces are set as free surfaces; the calculation amount is added, and the deformation amount of the diffusion layer is set to view the results.
[0040] Step 4: Obtain the displacement of the fuel cell diffusion layer;
[0041] Based on the simulation results in step 3, the deformation and displacement of the fuel cell diffusion layer caused by the encapsulation pressure are first obtained, and then the height of the diffusion layer under pressure below the flow channel ridge is obtained.
[0042] Step 5: Adjust the thickness of the fuel cell diffusion layer according to the deformation of the diffusion layer caused by the encapsulation pressure:
[0043] First, subtract the thickness of the diffusion layer below the flow channel ridge caused by the compression due to the encapsulation pressure from the original thickness of the fuel cell diffusion layer to obtain the height difference Δh.
[0044] Then optimize the thickness of the diffusion layer as follows: change the thickness of the diffusion layer at the contact position with the flow channel ridge to the original thickness plus the height difference Δh, which gives the optimized thickness of the diffusion layer at various points of the fuel cell with unequal thickness.
[0045] In the above, the method of increasing the thickness is to first process the diffusion layer according to the original thickness plus the height difference as the target thickness, and then process the diffusion layer to process the thickness of the position in the diffusion layer that does not contact the flow channel ridge to the original thickness, so that the initial thickness of the position in the diffusion layer that contacts the flow channel ridge is the original thickness plus the height difference.
[0046] Step 6: Test the optimized fuel cell and perform simulation calculations again to determine if the displacement of the diffusion layer after optimization has achieved the desired effect.
[0047] The displacement of the diffusion layer in the optimized proton exchange membrane fuel cell was detected to determine whether the diffusion layer of the optimized fuel cell could achieve a consistent thickness after being subjected to encapsulation pressure.
[0048] Step 7: If the goal of uniform thickness of the diffusion layer after pressure is not achieved, repeat the steps until the goal is achieved.
[0049] In this embodiment, a serpentine flow channel is selected for the bipolar plate flow channel of the three-dimensional proton exchange membrane fuel cell.
[0050] Furthermore, the overlap of the anode and cathode flow channels of the serpentine three-dimensional proton exchange membrane fuel cell bipolar plate is set to 100%, meaning that the ridges and flow channels of the anode and cathode are completely symmetrical.
[0051] The serpentine three-dimensional proton exchange membrane fuel cell geometric model includes bipolar plates, a diffusion layer, a catalyst layer, and a proton exchange membrane. Modeling was performed using SolidWorks, where each component is 40mm in length and width, and the thicknesses of the bipolar plates, diffusion layer, and proton exchange membrane are 2mm, 0.3mm, 0.02mm, and 0.05mm, respectively. The flow channel cross-section is a 1mm × 1mm square.
[0052] The geometric model of the serpentine three-dimensional proton exchange membrane fuel cell was meshed using Hypermesh, with 3D and 2D meshes created according to different components and boundary conditions.
[0053] Import the mesh file into Ansys and set the boundary and initialization conditions. Set the material properties of the bipolar plate, diffusion layer, catalyst layer, and proton exchange membrane; set the assembly pressure to be uniformly distributed on the upper and lower surfaces of the bipolar plate; set the left and right surfaces of the computational domain as symmetrical boundary conditions; set the other surfaces as free surfaces; and set the deformation of the diffusion layer to view the results.
[0054] After calculation, the displacement of the bipolar plate and diffusion layer of the fuel cell is obtained, including the diffusion layer displacement cloud map and displacement data.
[0055] The original fuel cell diffusion layer thickness is subtracted from the diffusion layer thickness below the flow channel ridge due to compression caused by the encapsulation pressure, resulting in a height difference Δh. The original thickness of the fuel cell diffusion layer below the flow channel ridge is then changed to the original thickness plus the height difference Δh, thus obtaining the optimized thickness of the fuel cell diffusion layer with unequal thickness at various points.
[0056] Perform optimized testing. Establish an optimized geometric model, which differs from the original model only in the thickness of the diffusion layer.
[0057] The optimized geometric model is then meshed, boundary conditions are set, initialization conditions are applied, and the model is calculated.
[0058] The optimization is completed based on whether the diffusion layer thickness in the simulation results is consistent. If the diffusion layer thickness is consistent, the optimization ends; if the diffusion layer thickness is not consistent, the optimization steps are repeated until the diffusion layer thickness is consistent.
[0059] There are many specific ways to implement this invention. The above description is only a preferred embodiment of this invention. It should be noted that for those skilled in the art, several improvements can be made without departing from the principle of this invention, and these improvements should also be considered within the scope of protection of this invention.
Claims
1. A method for optimizing the diffusion layer of a fuel cell based on encapsulation mechanics, characterized in that, Includes the following steps: Step 1: Establish a three-dimensional geometric model of a proton exchange membrane fuel cell: Step 2: Mesh the three-dimensional proton exchange membrane fuel cell geometric model: The geometric model of the three-dimensional proton exchange membrane fuel cell established in step 1 is meshed, specifically including the bipolar plate, diffusion layer, catalyst layer, and proton exchange membrane interior are meshed in 3D, and the boundaries of each part of the fuel cell are meshed in 2D. Step 3: Simulate and calculate the geometric model of the three-dimensional proton exchange membrane fuel cell: The three-dimensional proton exchange membrane fuel cell geometric model with mesh generation completed in step 2 is simulated and calculated. Step 4: Obtain the displacement of the fuel cell diffusion layer. Based on the simulation results in step 3, the deformation and displacement of the fuel cell diffusion layer caused by the encapsulation pressure are first obtained, and then the height of the diffusion layer under pressure below the flow channel ridge is obtained. Step 5: Adjust the thickness of the fuel cell diffusion layer according to the deformation of the diffusion layer caused by the encapsulation pressure: First, subtract the thickness of the diffusion layer below the flow channel ridge caused by the compression due to the encapsulation pressure from the original thickness of the fuel cell diffusion layer to obtain the height difference Δh. Then optimize the thickness of the diffusion layer as follows: change the thickness of the diffusion layer at the contact position with the flow channel ridge to the original thickness plus the height difference Δh, which gives the optimized thickness of the diffusion layer at various points of the fuel cell with unequal thickness. Step 6: Detect the optimized displacement of the fuel cell diffusion layer and perform simulation calculations again. Determine whether the displacement of the diffusion layer before and after optimization achieves the desired effect based on the simulation calculations. The displacement of the diffusion layer in the optimized proton exchange membrane fuel cell was detected to determine whether the diffusion layer of the optimized fuel cell can achieve a consistent thickness after being subjected to encapsulation pressure. Step 7: If the goal of uniform thickness of the diffusion layer after pressure is not achieved, repeat the steps until the goal is achieved.
2. The fuel cell diffusion layer optimization method based on encapsulation mechanics according to claim 1, characterized in that, The bipolar plate flow channel of the three-dimensional proton exchange membrane fuel cell in step 1 can be a serpentine flow channel, a parallel flow channel, an interdigitated flow channel, a spiral flow channel, a grid flow channel, or a biomimetic flow channel, etc.
3. The fuel cell diffusion layer optimization method based on encapsulation mechanics according to claim 1, characterized in that, In step 1, the bipolar plate flow channels of the three-dimensional proton exchange membrane fuel cell may have different degrees of overlap, that is, the ridges and flow channels of the anode and cathode are not completely symmetrical.
4. The fuel cell diffusion layer optimization method based on encapsulation mechanics according to claim 1, characterized in that, The dimensional data of each part of the three-dimensional proton exchange membrane fuel cell geometric model in step 1 are not unique and can be changed according to the actual situation.
5. The fuel cell diffusion layer optimization method based on encapsulation mechanics according to claim 1, characterized in that, Step 3 involves simulating the three-dimensional proton exchange membrane fuel cell geometric model obtained from the mesh generation in Step 2. Specifically, this includes changing the material properties of the bipolar plates, diffusion layer, catalyst layer, and proton exchange membrane; adding boundary conditions by setting uniformly distributed assembly pressure on the upper and lower surfaces of the bipolar plates, assuming symmetrical boundary conditions on the left and right surfaces of the computational domain, and setting other surfaces as free surfaces; adding computational variables by setting the deformation of the diffusion layer to view the results.
6. The fuel cell diffusion layer optimization method based on encapsulation mechanics according to claim 1, characterized in that, Step 4 yields the displacement of the fuel cell diffusion layer, including a diffusion layer displacement cloud map and displacement data.
7. The fuel cell diffusion layer optimization method based on encapsulation mechanics according to claim 1, characterized in that, The height added below the flow channel ridge of the fuel cell diffusion layer in step 5 is determined by the height by which the original diffusion layer was pressed down by the flow channel ridge.
8. The fuel cell diffusion layer optimization method based on encapsulation mechanics according to claim 1, characterized in that, The optimized fuel cell diffusion layer obtained in step 5 is a diffusion layer of unequal thickness, with a corrugated upper surface, meaning that the diffusion layer below the flow channel is thinner and the diffusion layer below the flow channel ridge is thicker.
9. The fuel cell diffusion layer optimization method based on encapsulation mechanics according to claim 1, characterized in that, In step 6, the only difference between the fuel cells before and after optimization, in terms of simulation conditions such as geometric parameters, boundary conditions, initialization conditions, and number of iterations, is the thickness of the fuel cell diffusion layer.