A systematic approach to simulation modelling and design of Proton Exchange Membrane Unitised Regenerative Fuel Cells with experimental comparison
Creators: name: ARIF, Muhammad
Publisher: name: RMIT University
Year: 2024
Subjects: classificationCode: 401703
subject: Energy generation, conversion and storage (excl. chemical and electrical)

description: Our communities, our health and our climate are being adversely affected by global warming (UCS 2018). According to the Climate Change 2014 Synthesis Report by Inter Governmental Panel on Climate Change IPCC (2014), rapid economic and population growth has led to the drastic increase in atmospheric concentration of  CO2 from 280 parts per million in 1850 to 400 parts per million  in 2014. IPCC (2014) estimated that around 40 Gigatonnes of CO2 emissions are caused by burning of fossil fuels, cementing and flaring in 2011. The issue of global warming needs speedy and effective actions by reducing greenhouse gas emissions (UCS 2018). The best way to reduce greenhouse gas emissions is to replace fossil fuels with renewable energy sources such as solar, wind, wave and tidal energy (Owusu et al. 2016). However, these sources are inherently variable and require energy storage to ensure a continuous and reliable supply.

Proton Exchange Membrane (PEM) Unitised Regenerative Fuel Cells (URFCs) are promising for use in zero-emission systems for storing renewable energy and re-supplying electricity. However, some significant issues like water flooding and thermal management need to be resolved before commercialisation. Fabrication and testing of Proton Exchange Membrane (PEM) fuel cells to improve performance is an expensive and time-consuming process. Tackling these issues through a combination of simulation and experimental testing can save both cost and time in optimising cell design and moving towards prototypes.
 
However, there are many gaps in knowledge and understanding relating to the simulation modelling of PEM fuel cells, including principally the following

- Difficulties have been encountered in modelling accurately the rapid voltage drop that occurs in fuel cell polarisation curves with increasing current density. The problems have arisen because of limitations in representing mass transport losses that occurs at high current densities due to a number of factors such as flooding of active sites of catalysts, blocking of pores of catalyst layers and GDLs by water, and resistance to the flow of oxygen due to the ionomer covering catalyst particles.

- Most of the researchers have calibrated simulation models against experimental data without following a systematic procedure. These ad hoc calibration procedures have been very time consuming. So, there is a lack of a step-by-step procedure to match a simulated and experimental polarisation curves.

- The values of several model input parameters such as exchange current density, charge transfer coefficient, protonic conduction coefficient, and etc are very hard to be found through independent experiments. Hence, there is a need to use the calibration of model against experimental results to estimate the best-fit values of these input parameters.

- While most of the papers have focused on studying the influence of different parameters (e.g.: catalyst properties, membrane conductivities, GDL wettability, channel configurations, operating conditions, and etc) on the performance of PEM fuel cells, there has been very little on using of the simulation modelling to diagnose the performance of already fabricated cells.

- Most of the research papers are focused on the dedicated modelling of single PEM Fuel cell, while work done on modelling URFC, even in fuel cell mode, has been extremely limited.

A number of softwares such as COMSOL, OPEN FOAM, STAR-CD and ANSYS PEM Fuel Cell Module are used nowadays for the modelling and simulations of PEM fuel cells. The ANSYS PEM Fuel Cell  Module is selected for the present  study because it has the capability of full 3D modelling  of all components in fuel cell, so it can completely represent the geometry and structure of an actual experimental fuel cell, and the properties of different components (Wu, X 2017). Moreover, fluent can solve the basic governing equations required to model the PEM fuel cell solely.


Unitised Regenerative Fuel Cells (URFCs) are considered as a key component in hydrogen-based electrical energy storage systems. A URFC uses the same cell to produce hydrogen fuel in electrolysis mode and generate electricity in fuel cell mode.  Multi-cell URFC stacks can provide electrical energy storage at larger scale. Therefore, modelling of multi-cell URFC stacks is becoming an emerging area in the designing of the URFC stacks.

This project, therefore, applies the ANSYS Fuel Cell Module to design optimisation of a single-cell URFC with the focus on fuel-cell-mode operation.

The aim of this project is to investigate the application of simulation modelling in design of single reversible fuel cells and small stacks operating in fuel cell mode.The principal research questions addressed are:

- To what degree can the ANSYS Fuel Cell Module accurately model the operation of a single-cell URFC, and give precise prediction to experimental data, with full consideration of mass transport losses?
- What step-by-step procedure is best applied in calibrating a Module simulation of a URFC in fuel cell mode to an experimental polarisation curve?
- How effective is the Module in the investigation of the factors limiting the performance of an existing single-cell PEM URFC in fuel cell mode?
- How effective is the Module as a tool for designing and optimising the performance of a single-cell PEM URFCs and small PEM URFCs stacks operating in fuel cell mode?
The principal expected beneficial outcomes are:
- Improved theoretical understanding and practical experience in applying theory-based simulation modelling to PEM URFCs as single cells and stacks of multiple cells.
- A systematic procedure for use of the ANSYS Fuel Cell for calibrating a Module simulation of a URFC in fuel cell mode to an experimental polarisation curve.
- Identification of the factors that are limiting the performance of the existing single-cell PEM URFC.
- Pointers towards optimised designs for a single-cell PEM URFCs and small PEM URFCs stacks operating in fuel cell mode developed using simulation modelling.

A novel step-by-step procedure is thus articulated in this thesis that can be applied to calibrate a simulation model of a PEM fuel cell, or URFC operating in fuel cell mode using an experimental polarisation curve. This systematic procedure can also be used to obtain the estimated values of the model input parameters such as exchange current density, charge transfer coefficient, protonic conduction coefficient, coefficient of liquid removal, exponents of pores blockage, and exponent of active site reductions that are not readily available and are hard if not possible to be measure experimentally.

By applying this systematic procedure, a good agreement was found between simulated and experimental polarisation curves. The polarisation curve obtained from the simulation data was able to detect the sharp turn down in the performance at higher current densities in the mass transport losses region, hence giving a good fit between simulated and experimental polarisation curves in the mass transport losses region. The accuracy of the match between simulated and experimental polarisation curves obtained by applying this systematic procedure was checked by using different statistical criteria such as; mean squared difference, sum of squared differences, and coefficient of determination (R2). For an experimental cell with an active area of 5 cm2 the maximum percentage difference value was 5% and the coefficient of determination (R2) between the simulated and experimental curves was 0.99, indicating a very close fit. If needed in future studies, the values of the maximum percentage difference can be further reduced, by varying other model input parameters that have so far been kept constant, including for example, the concentration dependence, and local species concentration reference values.

The uniqueness of the values of the input parameters obtained through calibration was checked by comparing the simulated curve using same set of input parameters with experimental polarisation curve operating at different conditions. The continued matching of the simulated and experimental polarisation curves under these different operating conditions, indicated a high probability that the estimated values of the input parameters that were not changed, being unique. The variation of other input parameters like exponents of pores blockage and exponents of covering of active sites of catalyst did not affect the output values of the current densities substantially, therefore the values of these input parameters were kept same as default values. This probability of estimated values being unique can be further increased in the future studies, if additional simulations with these inputs of the cell operating under different conditions again do not reveal significant differences between the resulting simulated and experimental curves.

After calibrating the simulation model against experimental results, the ANSYS PEM Fuel Cell Module was used for the diagnostic analysis of a single-cell PEM URFC that was designed and fabricated at RMIT University. By using the Module, the factors that were lowering the performance of this URFC in fuel cell mode were effectively identified.

The performance of the RMIT URFC was compared with that of a higher-performing URFC reported by Hwang et al. (2012). The diagnostic analysis of the RMIT URFC was carried out in two steps: firstly, the RMIT URFC was simulated using Hwang's URFC operating conditions to see the improvement in the performance; and then the values of input parameters (exchange current densities and protonic conduction coefficient) related to the characteristics of the cell components were varied.

By applying Hwang's operating conditions, the maximum power density value of the simulated RMIT URFC were doubled from 0.163 W/cm2 to 0.327 W/cm2. One of the reasons for high performance under Hwang's URFC operating conditions was the much higher cell temperature, which helped in evaporating the liquid water and thus reducing the mass transport losses. The higher stoichiometric ratio of inlet gases under Hwang's operating conditions prevented the cell from starvation at higher current densities, which means it was getting sufficient reactants and oxidants even at higher current densities. The inlet gases in the case of Hwang's URFC were more humid compared to the RMIT URFC, which kept the membrane hydrated and enhanced the membrane proton conductivity.
 
The simulated RMIT URFC was still performing lower than Hwang's URFC in the ohmic polarisation region even after applying the Hwang's operating conditions. To make the performance of the RMIT simulated URFC comparable to the Hwang's URFC in this region, the value of protonic conduction coefficient was increased from 1 to 1.5. The performance of the simulated RMIT URFC then more closely matched that of Hwang's URFC in this region. The relative humidities of the inlet gases in both URFCs were then same, and the thickness of the membranes for both URFCs was also the same because Nafion 115 membrane was used in both URFCs. Hence, the most likely reason for the lower membrane performance in the case of RMIT URFC was some form of degradation of the membrane that adversely affected its proton conductivity. The precise form of this degradation was not identified in the present work.

ANSYS PEM Fuel Cell Module was then used as a design tool to select the best-performing channel configurations for the fabrication of single-cell PEM URFC in fuel cell mode with an active area of 100 cm2 rather than fabricating and testing a number of cells each with a different channel configurations.
 
Four URFCs with different flow channel configurations i.e. single-channel serpentine, 2-channel serpentine, 3-channel serpentine and parallel channels were simulated under RMIT URFC operating conditions, using the ANSYS PEM Fuel Cell Module. Their performances were compared on the basis of maximum power density. According to the simulation results, the URFC with 3-channel serpentine configuration was the best design with better performance. The concentration of oxygen at catalyst membrane interface is higher in the regions that are under the channels. Since in the case of 3-channel serpentine the area of channels was larger therefore oxygen was more uniformly distributed over the catalyst layer. The current density values were consequently higher in the regions where the concentration of oxygen was higher. Hence oxygen was spread over the wide region of active area in the case of 3-channel serpentine configuration, therefore more current was generated. In addition, the pressure drop in this configuration was lower than single and double channel serpentine configuration, and hence less power would be required to blow the gases inside the channels.
 
In the next step, the 100 cm2 URFC with better performing i.e., 3-channel-serpentine configuration was simulated using Hwang's operating conditions. The simulation results showed 38% increase in the performance of 3-channels serpentine URFC under Hwang's operating conditions. The key reasons for the boost in the performance under Hwang's operating condition were the same as those identified in the diagnostic analysis of 5 cm2 single-cell PEM URFC: lower liquid saturation values at the channels/GDL interface due to higher cell temperature and the higher concentration of the oxygen at the catalyst due to higher stoichiometric ratio. On comparing the performance of the simulated 100 cm2 URFC with 3-channel serpentine configuration under Hwang's operating condition with Hwang's URFC, there was still 12.5% of deficit in the performance of the simulated URFC. This comparison was made on the basis of power per unit area and it should be noted that the Hwang's URFC has an active area of 27 cm2 while the simulated URFC is 100 cm2 .The difference in performance can be possibly due to difference in the active areas or due to lower membrane conductivity as it was concluded in the diagnostic analysis before.

Finally, two small URFC stacks each made from cells with 100 cm2 active area and 3-channels serpentine configuration consisting of two cells and five cells were simulated under Hwang's operating conditions to investigate how power output per unit active area varied with number of cells in a stack, as a guide in designing stacks with larger number of cells. The simulation results showed 3.3% performance drop the for two-cell stack and 6.7% drop for five-cell stack compared to the ideal case of maintaining the same power output per unit area obtained from a single-cell of the same design and area. From the simulation results it was found that the consumption rates of the air and hydrogen for the individual cells reduces as the number of cells per stack were increased.
 
The GDL properties such as hydrophobicity and porosity that are influencing the mass transport losses in the PEM fuel cell were also analysed in this thesis. The hydrophobicity of the GDL has been increased by increasing the values of contact angle within hydrophobic range. The simulation results have shown that by increasing the contact angles the performance increases till 150o and after that the performance remains the same. By increasing hydrophobicity, the rate of liquid water removal increased thus reducing the mass transport losses. Also, by increasing the porosity, the liquid removal rate and the diffusivity of species gases increased due to which the concentration of the species gases at electrodes becomes higher which results in lower mass transport losses and higher performance.
 
Sensitivity analysis of exponents related to the mass transport losses - i.e., exponent of pores blockage and exponent of covering of active sites of catalyst - was performed in this thesis.  The simulation results showed that by varying the values of exponent of pores blockage and exponent of covering of active sites of catalyst by 20% from the default value, the difference in the output values of current densities was not substantial i.e. maximum 2.6% .However, it was concluded that variation of values of exponents of pores blockage had more dominant effect on the polarisation curve than the exponents of the covering of active sites of catalyst.

The following recommendations are made relating to the further development of simulation and modelling of PEM fuel cells and URFCs.
- The simulation results obtained from the study in chapter 7 should be verified through experiments. 
- The modelling of URFCs in fuel cell mode should be extended to the simulation of the PEM URFCs in electrolyser mode also.
- The modelling and simulation should be further extended to the performance assessment of the larger stacks with 10-cells, 20 cells, 30-cells and more to see how the performance further drops with increase in the number of cells per stack. Design changes and operating conditions changes should be made to minimise this drop-in performance. 
- An algorithm should be developed and incorporated to the simulation codes that automatically and systematically matches simulated and experimental polarisation curves, in terms of reducing the percentage difference between simulated and experimental results. 
- The uniqueness of the best fit input parameters should be checked by comparing the simulated polarisation curves with more than two experimental curves operating at different set of operating conditions and cell design parameters for example: cell temperature, stochiometric ratios, relative humidities of the inlet gases, channel configurations and active area.
- In the diagnostic analysis, the cell should be tested experimentally under the optimal operating conditions and cell characteristics predicted by simulation modelling to check the improvement in performance. 
- Further work should be conducted into developing in situ techniques to calculate the values of the primary model input parameters such as exchange current densities and charge transfer coefficients experimentally. 
- PEM fuel cells with micro-porous layers should be simulated to investigate their effects on performance and optimise the characteristics of the MPL.