A method for online monitoring of water content in each layer of a fuel cell

Abstract

The present invention discloses an online monitoring method for the water content of each layer of a fuel cell, comprising: collecting initial real-time data of the fuel cell; inputting the initial real-time data into a state model, and combining the fourth-order Runge-Kutta method to monitor the water content of each layer of the fuel cell; wherein the state model utilizes the equilibrium relationship between water production and drainage of each layer of the fuel cell, and is constructed by combining electrochemical reaction water production, Fick diffusion, capillary pressure suction drainage, and flow channel outlet drainage. The advancement of the present invention is reflected in that it can not only directly obtain the water content inside the stack, but also obtain the water content of each layer of the fuel cell.

Description

Technical Field

[0001] The invention belongs to the technical field of fuel cells, and in particular relates to an online monitoring method for the water content of each layer of a fuel cell. Background Art

[0002] The normal operation of fuel cells requires real-time monitoring of internal water content to improve stability and reliability. At present, the main indicator for evaluating the real-time operating status of proton exchange membrane fuel cells is voltage. Maintaining the optimal water state of the fuel cell is the key to ensuring output performance and stable operation. The commonly used voltage inspection method currently indirectly reflects the internal water state, but the voltage change lags behind the change in water content. This method can only take control measures after judging that the output power has dropped, which is costly and has poor recovery effect.

[0003] The impedance method can determine the water content, but it requires the introduction of additional disturbances and has a high overall cost. Impedance is related to the water content inside the fuel cell. Researchers use high-frequency impedance to obtain internal resistance or use the low-frequency region of the electrochemical impedance spectrum to obtain mass transfer losses. Toyota uses AC impedance technology to detect internal water content, and some institutions have also developed high-frequency impedance detection equipment integrated with DC-DC controllers. The disadvantage of the impedance method is that it introduces external disturbances, making the detection equipment technology complex and expensive (especially multi-channel impedance detection), and online applications are restricted.

[0004] More importantly, the low-temperature rapid start-up problems and flooding problems during normal operation faced during the commercialization of fuel cells require not only monitoring of the water content inside the stack, but also accurate identification of the water content of each layer, such as the catalyst layer, proton exchange membrane, diffusion layer, and gas flow channel. Monitoring the water content of the catalyst layer and proton exchange membrane is particularly important, which directly determines the low-temperature shutdown strategy, low-temperature start-up strategy, and flooding recovery strategy. Unfortunately, current impedance monitoring can generally only qualitatively determine the water content of the stack, and cannot accurately distinguish the water content of a specific layer. Summary of the invention

[0005] In order to solve the above technical problems, the present invention proposes an online monitoring method for the water content of each layer of a fuel cell, which can monitor the water content of different layers of the proton exchange membrane, anode and cathode catalyst layer, cathode and cathode diffusion layer, and cathode and cathode gas flow channel in real time, providing technical support for the fuel cell operation management strategy.

[0006] To achieve the above object, the present invention provides an online monitoring method for the water content of each layer of a fuel cell, comprising:

[0007] Collect initial real-time data of the fuel cell;

[0008] The initial real-time data is input into the state model, and combined with the fourth-order Runge-Kutta method, the water content of each layer of the fuel cell is monitored; wherein the state model utilizes the equilibrium relationship between water production and drainage of each layer of the fuel cell, and is constructed by combining electrochemical reaction water production, Fick diffusion, capillary pressure suction drainage, and flow channel outlet drainage.

[0009] Optionally, the initial real-time data includes: cathode intake flow rate, anode intake flow rate, cathode exhaust flow rate, anode exhaust flow rate and operating current.

[0010] Optionally, constructing the state model includes:

[0011] Dividing the fuel cell into a preset layer structure, and dividing the preset layer structure into preset layer substructures;

[0012] Based on the preset layer substructure, obtaining a preset number of parameters;

[0013] Based on the preset number of parameters, the preset number of state models are constructed in combination with water production, drainage, electrochemical reaction water production, Fick diffusion, capillary pressure suction drainage and flow channel outlet drainage in each layer of the fuel cell.

[0014] Optionally, the preset layer structure includes: a proton exchange membrane, a cathode catalyst layer, an anode catalyst layer, a cathode diffusion layer, an anode diffusion layer, a cathode gas flow channel and an anode gas flow channel.

[0015] Optionally, the preset number of parameters includes: proton exchange membrane water content λ mem , water content of cathode catalyst layer polymer λ ccl , water vapor concentration in the cathode catalyst layer C ccl,v , liquid water concentration in cathode catalyst layer C ccl,l , water content of anode catalyst layer polymer λ acl , water vapor concentration in the anode catalyst layer C acl,v , liquid water concentration in the anode catalyst layer C acl,l , water vapor concentration in cathode diffusion layer C cgdl,v , cathode diffusion layer liquid water concentration C cgdl,l , water vapor concentration in the anode diffusion layer C agdl,v , liquid water concentration in the anode diffusion layer C agdl,l , Cathode gas flow channel water vapor concentration C cgc,v , liquid water concentration in cathode gas flow channel C cgc,l , water vapor concentration in anode gas flow channel C agc,v , Liquid water concentration in anode gas flow channel C agc,l .

[0016] Optionally, the state model includes: a proton exchange membrane water quantum model, a cathode catalyst layer polymer water quantum model, a cathode catalyst layer water vapor concentration sub-model, a cathode catalyst layer liquid water concentration sub-model, an anode catalyst layer polymer water quantum model, an anode catalyst layer water vapor concentration sub-model, an anode catalyst layer liquid water concentration sub-model, a cathode diffusion layer water vapor concentration sub-model, a cathode diffusion layer liquid water concentration sub-model, an anode diffusion layer water vapor concentration sub-model, an anode diffusion layer liquid water concentration sub-model, a cathode gas flow channel water vapor concentration sub-model, a cathode gas flow channel liquid water concentration sub-model, an anode gas flow channel water vapor concentration sub-model, and an anode gas flow channel liquid water concentration sub-model.

[0017] Optionally, the cathode catalyst layer polymer water-containing quantum model is:

[0018]

[0019] Among them, λ ccl is the water content of the cathode catalyst polymer, t is time, EW is the proton exchange membrane equivalent, ρ is density, mem is the proton exchange membrane, L is thickness, ccl is the cathode catalyst layer, i is the current density, F is the Faraday constant, D is the Fick diffusion coefficient, m represents the water transferred in the proton exchange membrane, L is the average thickness of the two adjacent components, S n,l is the conversion rate between polymer and liquid water in the porous medium of the catalyst layer, S n,v is the conversion rate of gaseous water between the polymer and the porous medium of the catalyst layer;

[0020] The cathode catalyst layer water vapor concentration submodel is:

[0021]

[0022] Among them, C ccl,v is the water vapor concentration in the cathode catalyst layer, v,eff represents the effective diffusion coefficient of water vapor, and cgdl represents the cathode diffusion layer;

[0023] The cathode catalyst layer liquid water concentration submodel is:

[0024]

[0025] Among them, C ccl,l is the liquid water concentration in the cathode catalyst layer, ν is the dynamic viscosity of liquid water, K c is the permeability, P c is the capillary pressure of the component.

[0026] Optionally, the water-containing quantum model of the anode catalyst layer polymer is:

[0027]

[0028] Among them, λ acl is the water content of the anode catalyst polymer, t is time, EW is the proton exchange membrane equivalent, ρ is density, mem is the proton exchange membrane, L is thickness, acl is the anode catalyst layer, i is the current density, F is the Faraday constant, D is the Fick diffusion coefficient, m represents the water transferred in the proton exchange membrane, L is the average thickness of the two adjacent components, S n,l is the conversion rate between polymer and liquid water in the porous medium of the catalyst layer, S n,v is the conversion rate of gaseous water between the polymer and the porous medium of the catalyst layer;

[0029] The anode catalyst layer water vapor concentration submodel is:

[0030]

[0031] Among them, C acl,v is the water vapor concentration in the anode catalyst layer, v,eff represents the effective diffusion coefficient of water vapor, and agdl represents the anode diffusion layer;

[0032] The anode catalyst layer liquid water concentration submodel is:

[0033]

[0034] Among them, C acl,l is the liquid water concentration in the anode catalyst layer, ν is the dynamic viscosity of liquid water, K c is the permeability, P c is the capillary pressure of the component.

[0035] Compared with the prior art, the present invention has the following advantages and technical effects:

[0036] Existing real-time monitoring methods for fuel cell stacks cannot directly obtain the internal water content. The voltage inspection method and the impedance method can only indirectly reflect the water content. The advancement of the present invention is that it can not only directly obtain the internal water content of the fuel cell stack, but also obtain the water content of each layer of the fuel cell.

[0037] The existing technology has the problem that it is difficult and incomplete to obtain the water content inside the fuel cell stack. The patent of this invention collects data through reasonable sensors and adopts advanced algorithms to solve the above problems.

[0038] The lumped parameter model of the existing fuel cell stack is relatively simple, and the reference degree of the water content obtained by solving it is not high. The present invention adopts a 7-layer fuel cell model and constructs a lumped parameter model in which 15 states change with time, taking into account all water states, and the reference degree of the obtained result is better. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0040] Figure 1 This is a flow chart of a method for online monitoring of water content in each layer of a fuel cell according to an embodiment of the present invention;

[0041] Figure 2 It is a schematic diagram of the real-time water content in the proton exchange membrane, the cathode catalyst layer polymer, and the anode catalyst layer polymer according to an embodiment of the present invention;

[0042] Figure 3 A schematic diagram of the real-time concentration of liquid water in the porous medium of the cathode catalyst layer and the porous medium of the anode catalyst layer according to an embodiment of the present invention;

[0043] Figure 4 FIG. 4 is a schematic diagram of an input current step according to an embodiment of the present invention. DETAILED DESCRIPTION

[0044] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0045] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0046] This embodiment proposes a method for online monitoring of the water content of each layer of a fuel cell. Figure 1 As shown, the following steps are included:

[0047] Collect initial data of fuel cells;

[0048] The initial data is input into a preset state model, and combined with the fourth-order Runge-Kutta method, the water content of each layer of the fuel cell is monitored; wherein the preset state model is constructed according to preset parameters.

[0049] Further, the initial data includes: cathode intake flow rate, anode intake flow rate, cathode exhaust flow rate, anode exhaust flow rate and operating current.

[0050] Furthermore, constructing a preset state model includes:

[0051] dividing the fuel cell into a predetermined layer structure, and dividing the predetermined layer substructure into predetermined layer substructures;

[0052] Based on the preset layer substructure, obtain preset parameters;

[0053] Based on the preset parameters, a preset state model is constructed.

[0054] Further, the preset layer structure includes: a proton exchange membrane, a cathode catalyst layer, an anode catalyst layer, a cathode diffusion layer, an anode diffusion layer, a cathode gas flow channel and an anode gas flow channel;

[0055] The fuel cell structure involving water transfer is broken down into proton exchange membrane, cathode catalyst layer polymer, cathode catalyst layer porous medium, anode catalyst layer polymer, anode catalyst layer porous medium, cathode diffusion layer, anode diffusion layer, cathode flow channel, and the amount of water in the anode flow channel. In particular, the anode and cathode catalyst layers are subdivided into catalyst layer polymers and catalyst layer porous media.

[0056] Furthermore, the preset parameters include: the water content of the proton exchange membrane λ mem , water content of cathode catalyst layer polymer λ ccl , water vapor concentration in the cathode catalyst layer C ccl,v , liquid water concentration in cathode catalyst layer C ccl,l , water content of anode catalyst layer polymer λ acl , water vapor concentration in the anode catalyst layer C acl,v , liquid water concentration in the anode catalyst layer C acl,l , water vapor concentration in cathode diffusion layer C cgdl,v , cathode diffusion layer liquid water concentration C cgdl,l , water vapor concentration in the anode diffusion layer C agdl,v , liquid water concentration in the anode diffusion layer C agdl,l , Cathode gas flow channel water vapor concentration C cgc,v , liquid water concentration in cathode gas flow channel C cgc,l , water vapor concentration in anode gas flow channel C agc,v , Liquid water concentration in anode gas flow channel C agc,l .

[0057] Taking into account the water production from interlayer electrochemical reaction, water carrying by electric drag, water transfer by Fick diffusion, and water transfer by capillary pressure difference, 15 mathematical models of state changes over time were constructed:

[0058] The rate of change of water content in the proton exchange membrane is the balance of the water content in the membrane and the adjacent two catalyst layers, Fick diffusion and electric drag:

[0059]

[0060] Wherein, EW is the proton exchange membrane equivalent, ρ is the density, L is the thickness, D is the Fick diffusion coefficient, L is the average thickness of two adjacent parts, i is the current density, F is the Faraday constant, t is the time, the subscript mem is the proton exchange membrane, ccl is the cathode catalyst layer, acl is the anode catalyst layer, and m represents the water transferred in the proton exchange membrane.

[0061] The change rate of water content on the cathode catalyst layer polymer is the balance of water produced by electrochemical reaction, electric drag water, Fick diffusion zone water, conversion of polymer and liquid water in the porous medium of the catalyst layer, and conversion of polymer and gaseous water in the porous medium of the catalyst layer:

[0062]

[0063] Among them, S n,l is the conversion rate between polymer and liquid water in the porous medium of the catalyst layer, S n,v is the conversion rate of gaseous water between the polymer and the porous medium of the catalyst layer.

[0064]

[0065]

[0066] Where s is the liquid water saturation in the porous medium, C is the substance concentration in the porous medium, γ is the phase change rate constant, the subscript eq is the equilibrium water content, sat is the saturated water vapor, cl is the catalyst layer, n is the water in the polymer, v is the gaseous water, l is the liquid water, and a is the water vapor activity, which is expressed as the ratio of the vapor concentration to the saturated vapor concentration at the current temperature.

[0067] The rate of change of water vapor concentration in the porous medium of the cathode catalyst layer is S n,v Balance of water in the Fick diffusion zone with the catalyst layer / gas diffusion layer:

[0068]

[0069] Wherein, the subscript v,eff denotes the effective diffusion coefficient of water vapor and cgdl denotes the cathode diffusion layer.

[0070] The rate of change of liquid water concentration in the porous medium of the cathode catalyst layer is S n,l The balance of water carrying rate with the capillary pressure of the catalyst layer / diffusion layer:

[0071]

[0072] Where, ν is the dynamic viscosity of liquid water, K c is the permeability, P c is the capillary pressure of the component:

[0073]

[0074] Among them, σ is the surface tension, θ is the static contact angle, and ε is the porosity of the porous medium. The capillary pressure expression will also be used in the expressions of the liquid water change rate of the anode catalyst layer, the liquid water change rate of the cathode diffusion layer, and the liquid water change rate of the cathode flow channel described later. When using them, σ, θ, and s need to be replaced by local coefficients (that is, the three parameters need to be added with corresponding subscripts).

[0075] Similar to the cathode catalyst layer, the change rates of the polymer water content, the water vapor concentration of the porous medium, and the liquid water concentration of the porous medium in the anode catalyst layer are expressed as:

[0076]

[0077]

[0078]

[0079] The change rate of water vapor concentration in the cathode diffusion layer is the Fick diffusion zone water of the catalyst layer / diffusion layer, the Fick diffusion zone water of the diffusion layer / gas flow channel, and the gas-liquid phase change rate S inside the diffusion layer. v,l The balance of the three:

[0080]

[0081] Wherein, the subscript eff,gdl is the effective diffusion coefficient of water vapor between the diffusion layer and the gas flow channel.

[0082]

[0083] Where R is the ideal gas constant, T is the temperature, and the subscripts cond,evap represent the evaporation process, i.e. the transformation of liquid water into gaseous water. Similarly, evap,cond represent the condensation process.

[0084] The change rate of liquid water concentration in the cathode diffusion layer is a function of the capillary water velocity in the catalyst layer / diffusion layer, the capillary water velocity in the diffusion layer / gas flow channel, and S v,l Balance:

[0085]

[0086] Similar to the cathode diffusion layer, the concentration change rates of water vapor and liquid water in the anode diffusion layer are expressed as:

[0087]

[0088]

[0089] The rate of change of water vapor concentration in the cathode gas flow channel is the balance between the gas flow in and out of the flow channel and the water vapor migration in the diffusion layer / flow channel:

[0090]

[0091] Where V is the flow rate, L ch is the flow channel length, h v is the water vapor convective mass transfer coefficient, H ch is the flow channel height, subscript cgc represents the cathode gas flow channel, subscript in represents the gas flow channel inlet, subscript out represents the gas flow channel outlet, subscript c represents the cathode, and subscript g represents the gas.

[0092] The rate of change of liquid water concentration in the cathode gas flow channel is the balance between the liquid water flow rate in the diffusion layer / gas flow channel and the liquid water flow rate at the gas flow channel outlet:

[0093]

[0094] Where μ is the dynamic viscosity, the subscript g represents gas, and l represents liquid.

[0095] Similar to the cathode flow channel, the change rates of water vapor concentration and liquid water concentration in the anode flow channel are expressed as:

[0096]

[0097]

[0098] The fourth-order Runge-Kutta method can be used to iteratively solve the 15 water states of the 7 layers of the fuel cell proton exchange membrane, anode and cathode catalyst layer, diffusion layer, and gas flow channel represented by x. The solution is as follows: Figure 2-4 As shown, the water state quantity of the 7 layers at any time is obtained.

[0099]

[0100] Where x = [λ mem ,λ ccl ,C ccl,v ,C ccl,l ,λ acl ,C acl,v ,C acl,l ,C cgdl,v ,C cgdl,l ,C agdl,v ,C agdl,l ,C cgc,v ,C cgc,l ,C agc,v ,C agc,l ] T ,

[0101]

[0102] Using the collected cathode and anode inlet flow rate V c,in,g 、Va,in,g , cathode anode exhaust flow rate V c,out,g 、V a,out,g , fuel cell operating current i, etc., and the fourth-order Runge-Kutta method is used to solve the ordinary differential equation about x, and the recursive formula of x at different times is obtained:

[0103]

[0104] Among them, k+1 represents the next moment, k represents the previous moment, and h is the calculation step length.

[0105] l1=f(x(k))

[0106]

[0107]

[0108] l4=f(x(k)+hl3)

[0109] The above are only preferred specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for online monitoring of water content in each layer of a fuel cell, characterized in that: include: Collect initial real-time data of the fuel cell; The initial real-time data includes: cathode intake flow rate, anode intake flow rate, cathode exhaust flow rate, anode exhaust flow rate and operating current; The initial real-time data is input into the state model, and the water content of each layer of the fuel cell is monitored in combination with the fourth-order Runge-Kutta method; wherein the state model is constructed by utilizing the balance relationship between water production and drainage of each layer of the fuel cell, combining water production by electrochemical reaction, Fick diffusion, capillary pressure suction drainage, and drainage at the flow channel outlet; Constructing the state model includes: Dividing the fuel cell into a preset layer structure, and dividing the preset layer structure into preset layer substructures; Based on the preset layer substructure, obtaining a preset number of parameters; Based on the preset number of parameters, the preset number of state models are constructed in combination with water production, drainage, electrochemical reaction water production, Fick diffusion, capillary pressure suction drainage and flow channel outlet drainage in each layer of the fuel cell.

2. The method for online monitoring of water content in each layer of a fuel cell according to claim 1, characterized in that: The preset layer structure includes: a proton exchange membrane, a cathode catalyst layer, an anode catalyst layer, a cathode diffusion layer, an anode diffusion layer, a cathode gas flow channel and an anode gas flow channel.

3. The method for online monitoring of water content in each layer of a fuel cell according to claim 1, characterized in that: The preset number of parameters includes: the water content of the proton exchange membrane λ mem , water content of cathode catalyst layer polymer λ ccl , water vapor concentration in the cathode catalyst layer C ccl,v , liquid water concentration in cathode catalyst layer C ccl,l , water content of anode catalyst layer polymer λ acl , water vapor concentration in the anode catalyst layer C acl,v , liquid water concentration in the anode catalyst layer C acl,l , water vapor concentration in cathode diffusion layer C cgdl,v , cathode diffusion layer liquid water concentration C cgdl,l , water vapor concentration in the anode diffusion layer C agdl,v , liquid water concentration in the anode diffusion layer C agdl,l , Cathode gas flow channel water vapor concentration C cgc,v , liquid water concentration in cathode gas flow channel C cgc,l , water vapor concentration in anode gas flow channel C agc,v , Liquid water concentration in anode gas flow channel C agc,l .

4. The method for online monitoring of water content in each layer of a fuel cell according to claim 3, characterized in that: The state model includes: a proton exchange membrane water-containing quantum model, a cathode catalyst layer polymer water-containing quantum model, a cathode catalyst layer water vapor concentration sub-model, a cathode catalyst layer liquid water concentration sub-model, an anode catalyst layer polymer water-containing quantum model, an anode catalyst layer water vapor concentration sub-model, an anode catalyst layer liquid water concentration sub-model, a cathode diffusion layer water vapor concentration sub-model, a cathode diffusion layer liquid water concentration sub-model, an anode diffusion layer water vapor concentration sub-model, an anode diffusion layer liquid water concentration sub-model, a cathode gas flow channel water vapor concentration sub-model, a cathode gas flow channel liquid water concentration sub-model, an anode gas flow channel water vapor concentration sub-model, and an anode gas flow channel liquid water concentration sub-model.

5. The method for online monitoring of water content in each layer of a fuel cell according to claim 3, characterized in that: The cathode catalyst layer polymer water-containing quantum model is: Among them, λ ccl is the water content of the cathode catalyst layer polymer, t is time, EW is the proton exchange membrane equivalent, ρ is density, mem is the proton exchange membrane, L is thickness, ccl is the cathode catalyst layer, i is the current density, F is the Faraday constant, D is the Fick diffusion coefficient, m represents the water transferred in the proton exchange membrane, is the average thickness of two adjacent parts, S n,l is the conversion rate between polymer and liquid water in the porous medium of the catalyst layer, S n,v is the conversion rate of gaseous water between the polymer and the porous medium of the catalyst layer; The cathode catalyst layer water vapor concentration submodel is: Among them, C ccl,v is the water vapor concentration in the cathode catalyst layer, v,eff represents the effective diffusion coefficient of water vapor, and cgdl represents the cathode diffusion layer; The cathode catalyst layer liquid water concentration submodel is: Among them, C ccl,l is the liquid water concentration in the cathode catalyst layer, ν is the dynamic viscosity of liquid water, K c is the permeability, P c is the capillary pressure of the component.

6. The method for online monitoring of water content in each layer of a fuel cell according to claim 3, characterized in that: The water-containing quantum model of the anode catalyst layer polymer is: Among them, λ acl is the water content of the anode catalyst layer polymer, t is time, EW is the proton exchange membrane equivalent, ρ is density, mem is the proton exchange membrane, L is thickness, acl is the anode catalyst layer, i is the current density, F is the Faraday constant, D is the Fick diffusion coefficient, m represents the water transferred in the proton exchange membrane, is the average thickness of two adjacent parts, S n,l is the conversion rate between polymer and liquid water in the porous medium of the catalyst layer, S n,v is the conversion rate of gaseous water between the polymer and the porous medium of the catalyst layer; The anode catalyst layer water vapor concentration submodel is: Among them, C acl,v is the water vapor concentration in the anode catalyst layer, v,eff represents the effective diffusion coefficient of water vapor, and agdl represents the anode diffusion layer; The anode catalyst layer liquid water concentration submodel is: Among them, C acl,l is the liquid water concentration in the anode catalyst layer, ν is the dynamic viscosity of liquid water, K c is the permeability, P c is the capillary pressure of the component.

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