Study on Assembly Mechanics and Its Effect on the Performance of Proton Exchange Membrane Fuel Cell
Bibliographic record
Abstract
Proton exchange membrane fuel cell (PEMFC) is an energy conversion device, which converts the chemical energy of fuels into electrical energy directly through electrochemical reactions, it has been considered as one of the most promising clean energy conversion devices widely because of its wide range of fuel sources, clean and free pollution, high operating current, can start-up quickly at room temperature and other advantages. All of components of a PEM fuel cell need to be assembled by exerting pressure from the outside, since the gas diffusion layer (GDL) is a porous structure and its elastic modulus is relatively small, during the process of exerting pressure, if the assembly pressure is too large, it will cause the GDL over deformation or even irreversible damage, thus reducing the gas transmission channel, increasing the mass transfer resistance, and even will damage the fuel cell components, shorten the lifetime of the fuel cell; in contrast, if the assembly pressure is too small, due to the poor contact between the bipolar plate and GDL, the contact resistance will increase, which will lead the reduce of the fuel cell efficiency, and the leak tightness of gas will not be guaranteed, there will be a risk of fuel gas leakage. In this paper, the numerical simulation method is used to simulatethe deformation of GDL under different assembly pressures, and the influence of transmission parameters such as GDL porosity and permeability caused by assembly pressure and its influence on the performance of PEMFC are studied in order to get the optimum pressure, making the best performance of PEMFC. The main work and achievements are as follows: The single channel PEMFC geometric model is established, and the numerical simulation is used to simulate, and the parameters such as porosity and permeability of PEMFC under different assembly pressures are calculated according to the empirical formula. When the assembly pressure from 0 to 3.0 MPa, the porosity decreased from the initial value of 0.78 to about 0.38; permeability also has an order of magnitude change; and the contact resistance decreases as the assembly pressure increases, but it decreases gradually; The finite element analysis (FEA) is used to analyze the effect of different assembly pressures on GDL deformation. The results show that, under the action of assembly pressure, the part of GDL, which under the bipolar plate ribs, will be deformed in different degrees, and the deformation on both sides is similar and obvious, the degree of deformation increases as the assembly pressure increases, while the part of GDL, which under the channel, is almost unchanged; Through the simulation, the distribution of the components concentration in the single channel PEMFC flow channel and the polarization curves under the assembly pressure are analyzed, and compares with different assembly pressures. Since the gas in the flow channel reacts in the catalyst layer, the gas concentration decreases along the flow direction under different assembly pressures. For the polarization curves, when the assembly pressure is between 0.5 to 1.0 MPa, the same operating voltage, the fuel cell current density is greater than the case of other pressures, and the fuel cell with the highest power under this pressure. Therefore, when the assembly pressure between 0.5-1.0 MPa, the single channel PEMFC performance is optimal.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".