Fatigue life prediction method and system of fuel cell stack under cross-scale multi-physical field coupling effect

Abstract

The invention discloses a method and a system for predicting the fatigue life of a fuel cell stack under a cross-scale multi-physical field coupling effect. The method comprises the following steps: establishing a three-dimensional model of a proton exchange membrane fuel cell stack; based on the three-dimensional model, establishing a finite element model of the proton exchange membrane fuel cell stack through grid division; carrying out multi-physics field simulation on the fuel cell at a micro scale to obtain parameters required by macroscopic multi-physics field modeling; based on the finite element model, considering various physical fields involved in the actual operation process of the proton exchange membrane fuel cell to perform coupling analysis calculation; calculating to obtain conditions of a temperature field, a stress field, current density distribution and the like in the fuel cell under the coupled physical field condition; and predicting the fatigue life of the fuel cell stack based on the stress field distribution in the cell. According to the method, the coupling effect of multiple physical fields of the proton exchange membrane fuel cell stack in the actual operation state is fully considered, and the stress field distribution in the stack is simulated by a more efficient and economical numerical simulation method, so that the fatigue life of the fuel cell stack is predicted more accurately and efficiently; the method provides a theoretical basis for the optimization design of the fuel cell stack, and has important practical significance.

Description

Technical Field

[0001] The present invention relates to a method and system for predicting the fatigue life of a fuel cell stack, and in particular to a method and system for predicting the fatigue life of a fuel cell stack under the action of cross-scale multi-physical field coupling. Background Art

[0002] The development of clean energy has received widespread attention, including solar energy, tidal energy, wind energy and hydrogen energy. Among them, proton exchange membrane fuel cells have gradually been recognized by major automobile manufacturers due to their simple principles, stable operation, low noise and high conversion rate. As a result, major automobile manufacturers have successively launched different models of fuel cell vehicles.

[0003] In the daily operation of fuel cell vehicles, the fuel cell stack is coupled with multiple physical fields, and the stress field inside the fuel cell presents extremely complex distribution characteristics, which leads to a sharp increase in the difficulty of predicting the fatigue life of the fuel cell stack. At present, most researchers use CDF software and FEM software to conduct virtual tests of fuel cells under electrochemical fields and thermal fields. Few studies involve the fatigue life of fuel cell stacks under the coupling of random vibration fields, magnetic fields and acoustic fields. There is no public technology to couple the micro-scale fuel cell parameters under multiple physical fields with the macro fuel cell fatigue life prediction model, resulting in a large deviation between the final life prediction results and the actual situation.

[0004] Therefore, it is necessary to find a method to accurately predict the fatigue life of fuel cell stacks under the coupling of cross-scale multi-physical fields. Summary of the invention

[0005] Purpose of the invention: The purpose of the present invention is to provide a method and system for predicting the fatigue life of a fuel cell stack under the coupling of cross-scale multi-physical fields, which fully considers the coupling of multi-physical fields of a proton exchange membrane fuel cell stack under actual operating conditions, and predicts the fatigue life of a fuel cell stack more accurately and efficiently.

[0006] Technical solution: The present invention comprises the following steps:

[0007] Establish a three-dimensional model of the fuel cell stack;

[0008] Based on the three-dimensional model, a finite element model of the fuel cell stack is established;

[0009] Perform multi-physics simulation on fuel cells at the microscopic scale to obtain the parameters required for macroscopic multi-physics modeling;

[0010] Based on the finite element model, the coupling analysis and calculation are carried out considering various physical fields involved in the actual operation of the fuel cell;

[0011] The temperature field, stress field and current density distribution inside the fuel cell under coupled physical field conditions are calculated;

[0012] The fatigue life of the fuel cell stack is predicted based on the stress field distribution inside the battery.

[0013] The three-dimensional model of the fuel cell stack includes: bipolar plates, cathode / anode flow channels, cathode / anode gas diffusion layers, cathode / anode catalyst layers and proton exchange membranes.

[0014] In the finite element model, the cathode / anode gas diffusion layer, the cathode / anode catalyst layer and the proton exchange membrane have different grid sizes.

[0015] In the finite element model, the bipolar plate is a solid grid, and the remaining components are fluid grids.

[0016] The multi-physical fields include: vibration field, magnetic field, acoustic field, temperature field, and electrochemical field.

[0017] The parameters required for the macroscopic multi-physical field modeling include: open circuit voltage, cathode / anode reference exchange current density, diffusion reference coefficient of each component gas, porosity of gas diffusion layer / catalytic layer, density of each component, specific heat capacity of each component, thermal conductivity of each component, and electrical conductivity of each component.

[0018] The process of obtaining the parameters required for the macroscopic multi-physics field modeling is as follows:

[0019] The microscopic multi-physics multiphase flow simulation is carried out by using the multi-component multi-phase pseudo-potential LB model. The multi-relaxation collision operator is used, and the evolution equation of the density distribution function of each component is described as:

[0020]

[0021] Among them, f and f eq They represent the density distribution function and the density equilibrium distribution function respectively, the subscript k represents each component, a and β represent along the a direction and along the β direction respectively; F k,a represents the force term in velocity space; δ t and e a Represent the time step and discrete velocity respectively; M and Λ represent the orthogonal transformation matrix and diagonal relaxation coefficient matrix respectively;

[0022] The evolution equation of the distribution function of the solution model of the magnetic field potential equation is described as:

[0023]

[0024] Among them, h represents the distribution function, h eq represents the equilibrium distribution function, which is defined as:

[0025]

[0026] Where φ is the magnetic field potential and wa is the weight coefficient;

[0027] For the acoustic field calculation, the acoustic pressure is obtained through the instantaneous pressure disturbance of the fluid, and the calculation expression is:

[0028] δp(x,t)=p(x,t)-p0

[0029] Where p0 is the static pressure of the fluid, i.e. the undisturbed pressure, and p(x,t) is the instantaneous pressure of the fluid, which can be obtained according to the linear equation of state:

[0030]

[0031] In the formula, p(x,t) and are the instantaneous density and speed of sound of the fluid respectively;

[0032] The discrete velocity model of D2Q5 is used to solve the temperature field, and the evolution equation of its temperature distribution function is:

[0033]

[0034] Among them, g and g eq represent the temperature distribution function and the temperature equilibrium distribution function respectively; N and Q represent the non-orthogonal transformation matrix and the relaxation coefficient matrix of the D2Q5 model respectively.

[0035] In the coupling analysis calculation, the assumptions for solving include:

[0036] a. Assume that the mixed gas is an ideal gas;

[0037] b. The flow is incompressible laminar;

[0038] c. The gas diffusion layer, catalyst layer and proton exchange membrane are uniform, isotropic porous media;

[0039] d. Ignore the effect of gravity.

[0040] The fatigue life prediction formula of the fuel cell stack is:

[0041]

[0042] Among them, α1 and α2 are material coefficients, and σ is the corrected mean stress;

[0043]

[0044] Among them, σ Y is the material yield limit, σa and σ m are the stress amplitude and average value solved, respectively.

[0045] A fatigue life prediction system for a fuel cell stack under the coupling of cross-scale multi-physical fields, comprising: a fuel cell stack three-dimensional model establishment module, a fuel cell stack finite element model establishment module, a module for obtaining parameters required for macroscopic multi-physical field modeling, a coupling analysis and calculation module, a module for calculating the temperature field, stress field and current density distribution inside the fuel cell, and a fuel cell stack fatigue life prediction module.

[0046] Beneficial effects: The present invention fully considers the coupling effect of cross-scale multi-physical fields of the proton exchange membrane fuel cell stack under actual operating conditions, and simulates the stress field distribution inside the stack with a more efficient and economical numerical simulation method, thereby more accurately and efficiently predicting the fatigue life of the fuel cell stack, providing a theoretical basis for the optimal design of the fuel cell stack, which has important practical significance. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0048] The present invention will be further described below in conjunction with the accompanying drawings.

[0049] like Figure 1 As shown, a method for predicting fatigue life of a fuel cell stack under cross-scale multi-physical field coupling of the present invention comprises the following steps:

[0050] Step 1, establish a three-dimensional model of a proton exchange membrane fuel cell stack; the three-dimensional model of a proton exchange membrane fuel cell stack includes: bipolar plates, cathode / anode flow channels, cathode / anode gas diffusion layers, cathode / anode catalyst layers, and proton exchange membranes.

[0051] Step 2: Based on the three-dimensional model established in step 1, a finite element model of the proton exchange membrane fuel cell stack is established by meshing; the finite element model uses hexahedral meshes for finite element division, and the gas diffusion layer, catalyst layer and proton exchange membrane have different mesh sizes. The bipolar plate component is a solid mesh, and the remaining components are fluid meshes.

[0052] Step 3: Perform multi-physics field simulation on the fuel cell at the microscopic scale to obtain the parameters required for macroscopic multi-physics field modeling; the multi-physics field includes: vibration field, magnetic field, acoustic field, temperature field, and electrochemical field.

[0053] The parameters required for macroscopic multi-physics modeling include: open circuit voltage, cathode / anode reference exchange current density, diffusion reference coefficient of each component gas, porosity of gas diffusion layer / catalytic layer, density of each component, specific heat capacity of each component, thermal conductivity of each component, and electrical conductivity of each component. The specific process of obtaining these parameters is as follows:

[0054] The multi-component multiphase pseudo-potential LB model is used to simulate the microscopic multi-physics multiphase flow with large density ratio and large viscosity ratio. Using the multi-relaxation collision operator, the evolution equation of the density distribution function of each component is described as:

[0055]

[0056] Among them, f and f eq They represent the density distribution function and the density equilibrium distribution function respectively, the subscript k represents each component, and a and β represent along the a direction and along the β direction respectively. k,a Represents the force term in velocity space. δ t and e a denote the time step and discrete velocity respectively. M and Λ denote the orthogonal transformation matrix and diagonal relaxation coefficient matrix respectively.

[0057] The evolution equation of the distribution function of the solution model of the magnetic field potential equation is described as:

[0058]

[0059] Among them, h represents the distribution function, h eq represents the equilibrium distribution function, which is defined as:

[0060]

[0061] Where φ is the magnetic field potential and wa is the weight coefficient.

[0062] For the acoustic field calculation, the acoustic pressure is obtained through the instantaneous pressure disturbance of the fluid, and the calculation expression is:

[0063] δp(x,t)=p(x,t)-p0

[0064] Where p0 is the static pressure of the fluid, i.e. the undisturbed pressure, and p(x,t) is the instantaneous pressure of the fluid, which can be obtained according to the linear equation of state:

[0065]

[0066] In the formula, p(x,t) and are the instantaneous density and speed of sound of the fluid, respectively.

[0067] The discrete velocity model of D2Q5 is used to solve the temperature field, and the evolution equation of its temperature distribution function is:

[0068]

[0069] Among them, g and g eq They represent the temperature distribution function and the temperature equilibrium distribution function respectively. N and Q are the non-orthogonal transformation matrix and relaxation coefficient matrix of the D2Q5 model respectively.

[0070] Step 4: Based on the finite element model established in step 2, a coupling analysis and calculation is performed considering various physical fields involved in the actual operation of the proton exchange membrane fuel cell; the coupling analysis and calculation is calculated by finite element software, wherein the assumptions for the solution include:

[0071] a. Assume that the mixed gas is an ideal gas;

[0072] b. The flow is incompressible laminar;

[0073] c. The gas diffusion layer, catalyst layer and proton exchange membrane are uniform, isotropic porous media;

[0074] d. Ignore the effect of gravity.

[0075] Step 5, calculating the temperature field, stress field and current density distribution inside the fuel cell under the coupled physical field condition;

[0076] Step 6: Based on the stress field distribution inside the battery in step 5, predict the fatigue life of the fuel cell stack. The fatigue life prediction formula of the fuel cell stack is:

[0077]

[0078] Among them, α1 and α2 are material coefficients, and σ is the corrected mean stress.

[0079]

[0080] Among them, σ Y is the material yield limit, σ a and σ m are the stress amplitude and average value solved, respectively.

[0081] The method proposed in the present invention fully considers the coupling effect of cross-scale multi-physical fields of the proton exchange membrane fuel cell stack under actual operating conditions, and simulates the stress field distribution inside the stack with a more efficient and economical numerical simulation method, thereby more accurately and efficiently predicting the fatigue life of the fuel cell stack, providing a theoretical basis for the optimal design of the fuel cell stack, which has important practical significance.

[0082] The present invention also provides a fatigue life prediction system for a fuel cell stack under cross-scale multi-physical field coupling, comprising:

[0083] Proton exchange membrane fuel cell stack three-dimensional model building module: build a three-dimensional model of the proton exchange membrane fuel cell stack;

[0084] Finite element model building module for proton exchange membrane fuel cell stack: Based on the three-dimensional model, the finite element model of the proton exchange membrane fuel cell stack is established through mesh division;

[0085] Module for obtaining parameters required for macroscopic multi-physics field modeling: multi-physics field simulation of fuel cells is performed at the microscopic scale to obtain parameters required for macroscopic multi-physics field modeling;

[0086] Coupling analysis and calculation module: Based on the finite element model, the coupling analysis and calculation are performed considering the various physical fields involved in the actual operation of the proton exchange membrane fuel cell;

[0087] Module for calculating the temperature field, stress field and current density distribution inside the fuel cell: Calculate the temperature field, stress field and current density distribution inside the fuel cell under the coupled physical field conditions;

[0088] Fuel cell stack fatigue life prediction module: predicts the fatigue life of the fuel cell stack based on the stress field distribution inside the battery.

[0089] Example

[0090] like Figure 1 As shown, the fatigue life prediction method of a fuel cell stack under the cross-scale multi-physical field coupling of this embodiment includes the following steps:

[0091] Step 1, using SOLIDWORKS software to establish a three-dimensional model of a proton exchange membrane fuel cell stack including: bipolar plates, cathode / anode flow channels, cathode / anode gas diffusion layers, cathode / anode catalyst layers, and proton exchange membranes, etc.;

[0092] Step 2: Based on the three-dimensional model established in step 1, a finite element model of the proton exchange membrane fuel cell stack is established by meshing using HYPERMESH software. The finite element model is divided using a hexahedral mesh, and the gas diffusion layer, catalyst layer, and proton exchange membrane have different mesh sizes. The bipolar plate component is a solid mesh, and the remaining components are fluid meshes.

[0093] Step 3, performing multi-physical field simulation on the fuel cell at the microscopic scale to obtain the parameters required for macroscopic multi-physical field modeling; the multiple physical fields include: vibration field, magnetic field, acoustic field, temperature field, and electrochemical field.

[0094] The process of obtaining the parameters required for macroscopic multi-physics field modeling is as follows:

[0095] The multi-component multiphase pseudo-potential LB model is used to simulate the microscopic multi-physics multiphase flow with large density ratio and large viscosity ratio. Using the multi-relaxation collision operator, the evolution equation of the density distribution function of each component is described as:

[0096]

[0097] Among them, f and f eq They represent the density distribution function and the density equilibrium distribution function respectively, the subscript k represents each component, and a and β represent along the a direction and along the β direction respectively. k,a Represents the force term in velocity space. δ t and e a denote the time step and discrete velocity respectively. M and Λ denote the orthogonal transformation matrix and diagonal relaxation coefficient matrix respectively.

[0098] The evolution equation of the distribution function of the solution model of the magnetic field potential equation is described as:

[0099]

[0100] Among them, h represents the distribution function, h eq represents the equilibrium distribution function, which is defined as:

[0101]

[0102] Where φ is the magnetic field potential, w a is the weight coefficient.

[0103] For the acoustic field calculation, the acoustic pressure is obtained through the instantaneous pressure disturbance of the fluid, and the calculation expression is:

[0104] δp(x,t)=p(x,t)-p0

[0105] Where p0 is the static pressure of the fluid, i.e. the undisturbed pressure, and p(x,t) is the instantaneous pressure of the fluid, which can be obtained according to the linear equation of state:

[0106]

[0107] In the formula, p(x,t) and are the instantaneous density and speed of sound of the fluid, respectively.

[0108] The discrete velocity model of D2Q5 is used to solve the temperature field, and the evolution equation of its temperature distribution function is:

[0109]

[0110] Among them, g and geq They represent the temperature distribution function and the temperature equilibrium distribution function respectively. N and Q are the non-orthogonal transformation matrix and relaxation coefficient matrix of the D2Q5 model respectively.

[0111] The parameter conditions for multi-physics field coupling calculation are shown in Table 1.

[0112] Table 1 Multi-physics field coupling calculation parameters

[0113]

[0114]

[0115] Step 4: Based on the finite element model established in step 2, coupled analysis and calculation are performed considering various physical fields involved in the actual operation of the proton exchange membrane fuel cell.

[0116] The assumptions for the solution include:

[0117] a. Assume that the mixed gas is an ideal gas;

[0118] b. The flow is incompressible laminar;

[0119] c. The gas diffusion layer, catalyst layer and proton exchange membrane are uniform, isotropic porous media;

[0120] d. Ignore the effect of gravity.

[0121] Step 5, using finite element software to calculate the temperature field, stress field, current density distribution, etc. inside the fuel cell under coupled physical field conditions;

[0122] Step 6: Based on the stress field distribution inside the battery in step 4, the fatigue life of the fuel cell stack is predicted. The specific formula is:

[0123]

[0124] Among them, α1 and α2 are material coefficients, and σ is the corrected mean stress;

[0125]

[0126] Among them, σ Y is the material yield limit, σ a and σ m are the stress amplitude and average value solved, respectively.

Claims

1. A method for predicting fatigue life of a fuel cell stack under cross-scale multi-physical field coupling, characterized in that: The following steps are involved: Establish a three-dimensional model of the fuel cell stack; Based on the three-dimensional model, a finite element model of the fuel cell stack is established; Perform multi-physics simulation on fuel cells at the microscopic scale to obtain the parameters required for macroscopic multi-physics modeling; Based on the finite element model, the coupling analysis and calculation are carried out considering various physical fields involved in the actual operation of the fuel cell; The temperature field, stress field and current density distribution inside the fuel cell under coupled physical field conditions are calculated; The fatigue life of the fuel cell stack is predicted based on the stress field distribution inside the battery.

2. The fatigue life prediction method of a fuel cell stack under cross-scale multi-physical field coupling according to claim 1 is characterized in that: The three-dimensional model of the fuel cell stack includes: bipolar plates, cathode / anode flow channels, cathode / anode gas diffusion layers, cathode / anode catalyst layers and proton exchange membranes.

3. The fatigue life prediction method of a fuel cell stack under cross-scale multi-physical field coupling according to claim 2 is characterized in that: In the finite element model, the cathode / anode gas diffusion layer, the cathode / anode catalyst layer and the proton exchange membrane have different grid sizes.

4. The fatigue life prediction method of a fuel cell stack under cross-scale multi-physical field coupling according to claim 3 is characterized in that: In the finite element model, the bipolar plate is a solid grid, and the remaining components are fluid grids.

5. The fatigue life prediction method of a fuel cell stack under cross-scale multi-physical field coupling according to claim 1 is characterized in that: The multi-physical fields include: vibration field, magnetic field, acoustic field, temperature field, and electrochemical field.

6. The fatigue life prediction method of a fuel cell stack under cross-scale multi-physical field coupling according to claim 5 is characterized in that: The parameters required for the macroscopic multi-physical field modeling include: open circuit voltage, cathode / anode reference exchange current density, diffusion reference coefficient of each component gas, porosity of gas diffusion layer / catalytic layer, density of each component, specific heat capacity of each component, thermal conductivity of each component, and electrical conductivity of each component.

7. The fatigue life prediction method of a fuel cell stack under cross-scale multi-physical field coupling according to claim 6 is characterized in that: The process of obtaining the parameters required for the macroscopic multi-physics field modeling is as follows: The microscopic multi-physics multiphase flow simulation is carried out by using the multi-component multi-phase pseudo-potential LB model. The multi-relaxation collision operator is used, and the evolution equation of the density distribution function of each component is described as: Among them, f and f eq They represent the density distribution function and the density equilibrium distribution function respectively, the subscript k represents each component, a and β represent along the a direction and along the β direction respectively; F k,a represents the force term in velocity space; δ t and e a Represent the time step and discrete velocity respectively; M and Λ represent the orthogonal transformation matrix and diagonal relaxation coefficient matrix respectively; The evolution equation of the distribution function of the solution model of the magnetic field potential equation is described as: Among them, h represents the distribution function, h eq represents the equilibrium distribution function, which is defined as: Where φ is the magnetic field potential and wa is the weight coefficient; For the acoustic field calculation, the acoustic pressure is obtained through the instantaneous pressure disturbance of the fluid, and the calculation expression is: δp(x,t)=p(x,t)-p0 Where p0 is the static pressure of the fluid, i.e. the undisturbed pressure, and p(x,t) is the instantaneous pressure of the fluid, which can be obtained according to the linear equation of state: In the formula, p(x,t) and are the instantaneous density and speed of sound of the fluid respectively; The discrete velocity model of D2Q5 is used to solve the temperature field, and the evolution equation of its temperature distribution function is: Among them, g and g eq represent the temperature distribution function and the temperature equilibrium distribution function respectively; N and Q represent the non-orthogonal transformation matrix and the relaxation coefficient matrix of the D2Q5 model respectively.

8. The method for predicting fatigue life of a fuel cell stack under cross-scale multi-physical field coupling according to claim 7, characterized in that: In the coupling analysis calculation, the assumptions for solving include: a. Assume that the mixed gas is an ideal gas; b. The flow is incompressible laminar; c. The gas diffusion layer, catalyst layer and proton exchange membrane are uniform, isotropic porous media; d. Ignore the effect of gravity.

9. The method for predicting fatigue life of a fuel cell stack under cross-scale multi-physical field coupling according to claim 8, characterized in that: The fatigue life prediction formula of the fuel cell stack is: Among them, α1 and α2 are material coefficients, and σ is the corrected mean stress; Among them, σ Y is the material yield limit, σ a and σ m are the stress amplitude and average value solved, respectively.

10. A fatigue life prediction system for a fuel cell stack under cross-scale multi-physics field coupling, characterized in that: include: Fuel cell stack three-dimensional model building module, fuel cell stack finite element model building module, macro multi-physics field modeling required parameter acquisition module, coupling analysis calculation module, fuel cell internal temperature field, stress field and current density distribution calculation module and fuel cell stack fatigue life prediction module.

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