Embodiments relate generally to one or more methods for designing fuel cell flow fields for optimized reaction-fluid performance.
Microreactors (e.g., fuel cells) are widely used in energy storage and conversion systems whose flow fields play a significant role in their reaction-fluid performances.
A continuous-flow microreactor is an instrument that processes electro-chemical reactions with microchannel networking. It enables flow chemistry that cannot be done in batch. Microreactor technologies reveal a host of performance benefits enabled by the adoption of engineered microchannel fluid flow structures in biomedical, pharmaceutical and energy sectors.
Inside fuel cell stacks, starting reactants (i.e., air and hydrogen) are fed at the inlets by pumping and distributed via microchannel flow fields. The optimal design of flow fields plays a significant role in fuel cell performances.
Typical fuel cell flow fields are designed using forward design methods, where the flow path layout is fixed, and the size of pathways may be optimized to meet system requirements. This type of design method heavily depends on the initial layout, which is selected by the designer a priori. There are numerous examples of flow fields optimized using forward design to create pin, parallel, serpentine, interdigitated and mesh structures.
Researchers have also drawn inspiration from biology to design novel flow fields, including tree, lung, and fractal structures.
To facilitate out-of-the-box innovative designs, inverse design methods can be used, where the topology of the flow network is not defined a priori. The flow field design can be formulated as a material (i.e., fluid channel or wall) distribution problem. Optimization iterations are then used to arrive at a channel layout by minimizing target design objectives while performing physics simulations and sensitivity analysis. As an inverse design method, topology optimization has been applied to design microfluidic reactors, microbioreactors, hydrogen fuel cells, and redox flow batteries with significant reaction-fluid performance improvement when compared with conventional, forward designed reactors. Direct topology optimization methods where the material distribution at every discretized element (or node) is designed, however, require high computational cost and are often constrained to simple (i.e., limited channel number) academic problems.
In previous design methods, the isotropic permeability and infinite depth in the channel height dimension are assumed. The isotropic permeability assumption, however, can only be realized with highly discretized wall features (e.g., short Turing patterns).
To address the aforementioned limitations, one or more embodiments set forth, described, and/or illustrated herein exploits an anisotropic porous media optimization and dehomogenization framework to design fuel cell flow fields. By abandoning the explicit modeling of channels during the optimization stage, which requires a large number of function evaluations, the physics inside anisotropic porous media can be captured with relatively coarse discretization of the design domain. The development of intricate space-filling microchannels in a refined domain discretization is performed only once to recover the optimized anisotropic porous media. As a result, the channel synthesis is scalable in a computationally efficient manner.
To design more continuous flow fields, which are favored by many fuel cell applications, the one or more embodiments provides for an anisotropic porous media design method with high contrast permeabilities along and which are perpendicular to the channel direction. To address the shallow depth nature in fuel cells and the effect of the diffusion layer, the one or more embodiments uses unit cell modeling to capture the three-dimensional (3D) out-of-plane effect. Through a diagonal inlet-outlet flow configuration example, both the reaction and fluidic performances are optimized simultaneously by applying a multi-objective algorithm. It is demonstrated that the optimized flow fields outperform (i.e., Pareto dominate) benchmark parallel and serpentine designs.
In accordance with one or more embodiments, fuel cell stacks comprise: one or more bipolar plates having a fuel cell bipolar plate body with an inlet region, an outlet region, a reaction region arranged between and fluidically connected to the inlet region and the outlet region, and one or more microchannel fluid flow networks extending from the inlet region to the outlet region. The microchannel fluid flow networks include a plurality of primary flow microchannels having one or more secondary flow microchannels branching therefrom to facilitate reaction uniformity and reduce fluid flow resistance through the fuel cell.
In accordance with one or more embodiments, fuel cell stacks comprise: one or more bipolar plates having a fuel cell bipolar plate body with an inlet region, an outlet region, a reaction region arranged between and fluidically connected to the inlet region and the outlet region, and one or more microchannel fluid flow networks extending from the inlet region to the outlet region. The microchannel fluid flow networks include a plurality of primary flow microchannels of varying channel length to direct fuel reactants towards the outlet region and one or more secondary flow microchannels of varying channel length branching from the primary flow microchannels in a dendritic manner to facilitate reaction uniformity and reduce fluid flow resistance through the fuel cell.
In accordance with one or more embodiments, a bipolar plate for fuel cells comprises: a bipolar plate body with an inlet region, an outlet region, a reaction region arranged between and fluidically connected to the inlet region and the outlet region, and one or more microchannel fluid flow networks extending from the inlet region to the outlet region. The microchannel fluid flow networks include a plurality of primary flow microchannels having one or more secondary flow microchannels branching therefrom to facilitate reaction uniformity and reduce fluid flow resistance through the fuel cell.
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The illustrated example embodiments are intended for purposes of illustration only, and not limited thereto. The various advantages of the embodiments of will become apparent to one skilled in the art by reading the following specification and appended claims, and by referencing the following drawings, in which:
In accordance with one or more embodiments, an inverse design method used to design a fuel cell having an optimized microchannel design. In implementation of the design, initially, a spatially varying two-dimensional (2D) orientation field of the homogenized anisotropic porous media is optimized using an iterative, gradient-based algorithm. A time-dependent reaction-diffusion system is then applied to dehomogenize the optimized anisotropic porous media and synthesize 3D microchannel flow networks.
The parameterization of the orientation field follows the orientation tensor method previously proposed for elastic composite design problems. In a prescribed design domain, the orientation at a point in 2D space is represented by an orientation tensor, a, which is related to an orientation vector, p=(p1, p2), as follows:
A 2×2 symmetric matrix field variable q=(qij)→(aij) with qij∈[0,1] is used as the design variable, which can be regularized with a Helmholtz PDE filter as follows:
−r2∇2{tilde over (q)}ij+{tilde over (q)}ij={tilde over (q)}ij, (2)
where the filter radius r determines the overall smoothness of the designed orientation, and {tilde over (q)}ij is the regularized design variable.
The orientation tensor a can be written as follows:
where H is a smoothed step function, which projects {tilde over (q)}ij to be bounded between 0 and 1. N is a transformation function for the hypercube-to-simplex projection (HSP) scheme, which transforms a box domain to a triangular domain in 2D. Let ξ=H({tilde over (q)}11) and η=H({tilde over (q)}22), the HSP scheme can be written as follows:
Two tensor invariant conditions have to be satisfied in order to make an orientation tensor.
I
1
=tr(a)=a11+a22=1, (6a)
I
2=det(a)=a11a22−a122=0. (6b)
After applying the HSP scheme, the inequality constraint a11+a22≤1 is always satisfied. An additional global integral constraint is introduced the enforce the first tensor invariant condition as follows:
∫D(1−a11−a22)2dΩ−ϵ1≤0, (7)
where ϵ1 is an infinitesimal value.
In order to satisfy the second invariant condition, H({tilde over (q)}12) has to be either 0 or 1. To achieve this, another global integral constraint is introduced as follows:
∫D4H({tilde over (q)}12)(1−H({tilde over (q)}12))dΩ−ϵ2≤0, (8)
where ϵ2 is also an infinitesimal value.
The global second-rank permeability tensor, K, of an anisotropic porous medium rotated by the orientation tensor, a, is interpolated as follows:
K(1) is the local permeability in the major flow direction along the microchannel, and K(2) is the local permeability in the minor flow direction orthogonal to the microchannel. Both will be obtained via a local-level unit cell analysis, and Darcy's law is used to compute the effective porous medium permeability.
where v(n) is the unit cell inlet velocity, μ is the fluid dynamic viscosity, L(n) is the unit cell length, and Δp(n) is the pressure drop.
The simplified governing physics inside FC stacks can be modeled with Navier-Stokes equations and advection-diffusion-reaction equations. The steady-state anisotropic fluid flow physics is assumed to be incompressible and laminar. Chemical reaction is assumed to be proportional to the reactant concentration.
The anisotropic fluid flow physics is governed by the Navier-Stokes equations as follows:
ρ(u·∇)u=−∇p+∇·(μ(∇u+(∇u)T))−(μK−1)u, (12a)
∇·u=0, (12b)
where ρ, μ, u, and p are the fluid density, dynamic viscosity, velocity vector (state variable) and pressure (state variable).
To model the reaction physics, the solved fluid velocity vector, u, is coupled with the advection-diffusion-reaction equations:
∇·(−D∇c)+u·∇c=R, (13a)
R=−βc, (13b)
where, c, is the concentration (state variable), R is the local reaction rate assumed proportional to the concentration, D is the diffusion coefficient, and β is the reaction rate.
To design efficient, high-performing, and reliable FC stacks, the identified objectives comprise overall reaction performance (i.e., enhanced reaction uniformity though the fuel cell) and fluid flow performance (i.e., reduced fluid flow resistance though the fuel cell). By enhancing the reaction uniformity across the design domain, the reaction area is utilized more efficiently, which often increases the total overall reaction through the fuel cell and enhances long-term system reliability. By reducing or otherwise minimizing the flow resistance, less pumping power is required, which enhances the system efficiency.
The reaction uniformity objective f1 and the flow resistance objective f2 are formulated as follows:
The multi-objective optimization of anisotropic porous media is formulated as follows:
where w1 and w2 are weighting factors for the reaction uniformity and flow resistance design objectives. Different weighting factor settings can lead to various designs with trade-offs between the design objectives. ϵ1 and ϵ2 are infinitesimal values to ensure the two tensor invariant conditions, which can be gradually reduced in a continuation scheme during optimization.
A reaction-diffusion system is used to dehomogenize the optimized orientation field with microchannels. Its mathematical model involves two interacting hypothetical chemical substances whose concentrations are u and v. Their time-dependent local diffusion, reaction and replenishment can be described as follows:
Du and Dv are diffusion tensors perturbed over time with a strong anisotropic state. The principal axis of the anisotropic diffusion tensor is aligned with the optimized orientation in anisotropic porous media. The diffusion tensors using the optimized orientation tensor ā can be written as follows:
D
u(ā)=(wuw)2{lu2ā+I}, (18a)
D
v(ā)=(wvw)2{lv2ā+I}, (18b)
where lu and lv control the magnitude of anisotropy and wu and wv control the pitch of the microchannels. By specifying the channel pitch, w=wc+ww, the lateral magnitude of the diffusion, is proportional to w2. As a result, the prescribed unit cell geometry can be recovered.
In the illustrated example of
The effective anisotropic porous medium permeability given the geometric constraints is estimated using two separate local unit cell analyses. The geometry and boundary conditions for each example are presented in
Following Darcy's law (Eq. (11)), the effective permeability in the major flow direction along the microchannel, K(1), and the permeability in the minor or secondary flow direction orthogonal to the microchannel, K(2), can be computed.
The COMSOL-Matlab interface was used to determine the tradeoff between the competing objectives by assigning different weighting factors in the multi-objective function. Four example optimized anisotropic porous media results and the corresponding dehomogenized microchannel flow networks are illustrated in
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The reaction uniformity is measured by the average reactant concentration variation (left y-axis), the total reaction is measured by the average reactant concentration (right y-axis), and the flow resistance is measured by the total pressure drop (x-axis). The reaction-fluid performance of the example optimized microchannel designs outperforms the baseline parallel channel design and the baseline serpentine channel design.
The illustrated example of
As illustrated in
In one or more embodiments, the secondary flow microchannels 152 branch off from the primary flow microchannels 151 in a dendritic manner, thus forming a microchannel fluid flow network 150 having a biomimetic microstructure configuration that may be selectively designed to satisfy different aspects of design requirements and performance objectives of the fuel cell. Although the == of the illustrated example is designed to facilitate minimized fluid flow resistance, embodiments are not limited thereto. For example, the overall number and channel length of the primary flow microchannels 151 and secondary flow microchannels 152 may be selectively adjusted in the design phase in a manner which collectively form a geometric pattern or configuration that prioritizes: reaction uniformity of the fuel cell (
In accordance with one or more embodiments, an inverse design and dehomogenization framework for designing fuel cell flow fields having the optimized reaction-fluid performance. The weighted multi-objective optimization was solved by applying a gradient-based algorithm. To design spatially varying orientations, orientation tensor elements are parameterized and used as design variables. Local tensor invariant conditions are formulated as global integral constraints. To translate the optimized channel flow orientations into intricate microchannel designs, a reaction-diffusion system is used to dehomogenize the anisotropic porous media and obtain a plurality of optimized microchannel designs. Clear trade-offs between reaction performance and fluidic performance are observed, and hierarchical flow fields, comprising a plurality of primary flow microchannels and secondary flow microchannels, similar to biomimetic or nature systems (e.g., lungs, leaves and blood vessels) are generated using an inverse design framework. The amount and degree of secondary branching of flow fields may be controlled by weighting factor settings in the multi-objective optimization algorithm. Conventional parallel and serpentine flow field designs were outperformed by the inversely designed optimized flow fields (i.e., Pareto domination).
The terms “coupled,” “attached,” or “connected” may be used herein to refer to any type of relationship, direct or indirect, between the components in question, and may apply to electrical, mechanical, fluid, optical, electromagnetic, electromechanical or other connections. In addition, the terms “first,” “second,” etc. are used herein only to facilitate discussion, and carry no particular temporal or chronological significance unless otherwise indicated.
Those skilled in the art will appreciate from the foregoing description that the broad techniques of the one or more embodiments can be implemented in a variety of forms. Therefore, while the embodiments are set forth, illustrated, and/or described in connection with particular examples thereof, the true scope of the embodiments should not be so limited since other modifications will become apparent to the skilled practitioner upon a study of the drawings, specification, and claims.