Proton Exchange Membrane Fuel Cell Model Research Articles

Challenges and opportunities in modelling of proton exchange membrane fuel cells (PEMFC)

Challenges and opportunities in modelling of proton exchange membrane fuel cells (PEMFC)

Dynamic fuzzy cognitive network approach for modelling and control of PEM fuel cell for power electric bicycle system

Modelling Proton Exchange Membrane Fuel Cell (PEMFC) is the fundamental step in designing efficient systems for achieving higher performance. Among the development of new energy technologies, modelling and optimization of energy processes with pollution reduction, sufficient efficiency and low emission are considered one of the most promising areas of study. Despite affecting factors in PEMFC functionality, providing a reliable model for PEMFC is the key of performance optimization challenge. In this paper, fuzzy cognitive map has been used for modelling PEMFC system that is directed to provide a dynamic cognitive map from the affecting factors of the system. Controlling and modification of the system performance in various conditions is more practical by correlations among the performance factors of the PEMFC derived from fuzzy cognitive maps. On the other hand, the information of fuzzy cognitive map modelling is applicable for modification of neural networks structure for providing more accurate results based on the extracted knowledge from the cognitive map and visualization of the system’s performance. Finally, a rule based fuzzy cognitive map has been used that can be implemented for decision-making to control the system. This rule-based approach provides interpretability while enhancing the performance of the overall system.

Multi-objective optimization of operating conditions and channel structure for a proton exchange membrane fuel cell

In this study, the operating condition (operating temperature, anode pressure, cathode pressure and current density) and channel structure (heights of channel inlet and outlet) of a proton exchange membrane fuel cell (PEMFC) are optimized using multi-objective genetic algorithm. The optimizations of the operating condition and channel structure are based on a PEMFC stack model and a three-dimensional, steady-state, non-isothermal PEMFC model, respectively. The optimal operating condition and channel structure are selected by TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) from the optimal solution set called Pareto front. After the optimized operating condition is obtained, it is applied to the optimization of the channel structure. The results present that the optimal channel structure under the optimal operating condition is a type of tapered channel. Compared to the conventional straight channel, the tapered channel can enhance gas reactant transport in the PEMFC and a greater amount of reactant can participate in the electrochemical reaction, thus, more output power can be obtained.

Proton Exchange Membrane Fuel Cell Emulator Using PI Controlled Buck Converter

Alternative energy technologies are being popular for power generation applications nowadays. Among others, Fuel cell (FC) technology is quite popular. However, the FC unit is costly and vulnerable to any disturbances in input parameters. Thus, to perform research and experimentation, Fuel cell emulators (FCE) can be useful. FCEs can replicate actual FC behavior in different operating conditions. Thus, by using it the application area can be determined. In this study, a FCE system is modelled using MATLAB/Simulink®. The FCE system consists of a buck DC-DC converter and a proportional integral (PI) based controller incorporating an electrochemical model of proton exchange membrane fuel cell (PEMFC). The PEMFC model is used to generate reference voltage of the controller which takes the load current as a requirement. The characteristics are compared with Ballard Mark V 5kW PEMFC stack specifications obtained from the datasheet. The results show that the FCE system is a suitable replacement of real PEMFC stack and can be used for research and development purpose.

Validation of a methodology for determining the PEM fuel cell complex impedance modelling parameters

In this paper, we present a new methodology for determining the complex impedance parameters for a Proton Exchange Membrane (PEM) Fuel Cell in order to have a general model for embedded diagnosis. The modelling of Fuel Cells is a very important phase because it contributes to a better understanding and representation of the internal phenomena in this type of generator. After obtaining the experimental results of the complex impedance using a realized test bench for Proton Exchange Membrane (PEM) Fuel Cell using an electrochemical method which is the electrochemical impedance spectroscopy (EIS), we treat these results with an identification algorithm based on least squares method in the objective to determine the variations laws of the complex impedance parameters then implement in a PEM Fuel Cell model with Matlab/Simulink software. The established model of the complex impedance is based on electrical components and takes into account the mathematical equations of the different elements. The simulation results of this implemented model inform us about the state of the PEM Fuel Cell and validate the choice of the parameters. The validation of this choice is done by a comparative study using residual analysis method between the experimental and the simulation results. The general model is obtained from the superposition of the measured and theoretical results.

Efficient Voltage Control in Proton Exchange Membrane Fuel Cell: An Approach based on Intelligent Algorithms

ABSTRACTThe fuel cells, as the recently emerged power sources, offer a number of unique benefits such as higher efficiency, lower environmental impacts, and suitable scalability. These merits are achieved by devising accurate and efficient control mechanisms adopted for enhanced technical performances. Evidently, rapid voltage variations and a slow dynamic response are recognized as important challenges for an efficient voltage control mission in fuel cells. To overcome such issues, the ongoing study addresses the design procedure and numerical validation of an intelligent approach to enhance the voltage control process in a proton exchange membrane fuel cell (PEMFC) assembly. The implemented approach deploys the bacterial foraging algorithm (BFA) as the intelligent optimization engine. In mathematical statements, a complete modeling of PEMFC is first developed and then investigated thoroughly. To provoke an easy-implementable and trustable industrial controller, the renowned lead–lag controller is allocated herein. As the initial step, the established controller is tuned for a fixed operating point. Such practice, although reveals a good knowledge regarding the current state of the whole system, depreciates its performance in changing conditions. Thus, the second stage deploys the established BFA to optimally tune the controller against the changing conditions and faults happenings. Extensive numerical studies are carried out to assess the performance of the proposed controller. Results are discussed in depth.

Control of the Air Supply Subsystem in a PEMFC with Balance of Plant Simulation

This paper deals with the design of a control scheme for improving the air supply subsystem of a Proton Exchange Membrane Fuel Cell (PEMFC) with maximum power of 65 kW. The control scheme is evaluated in a plant simulator which incorporates the balance of plant (BOP) components and is built in the aspenONE® platform. The aspenONE® libraries and tools allows introducing the compressor map and sizing the heat exchangers used to conduct the reactants temperature to the operating value. The PEMFC model and an adaptive controller were programmed to create customized libraries used in the simulator. The structure of the plant control is as follows: the stoichiometric oxygen excess ratio is regulated by manipulating the compressor power, the equilibrium of the anode-cathode pressures is achieved by tracking the anode pressure with hydrogen flow manipulation; the oxygen and hydrogen temperatures are regulated in the heat exchangers, and the gas humidity control is obtained with a simplified model of the humidifier. The control scheme performance is evaluated for load changes, perturbations and parametric variations, introducing a growing current profile covering a large span of power, and a current profile derived from a standard driving speed cycle. The impact of the control scheme is advantageous, since the control objectives are accomplished and the PEMFC tolerates reasonably membrane damage that can produce active surface reduction. The simulation analysis aids to identify the safe Voltage-Current region, where the compressor works with mechanical stability.

Estimation of the Cathodic Overpotential for the Double Layer Structure in Pemfcs Using MD

In this work a molecular dynamics (MD) based model is employed to describe and obtain the over-potential in the EDL cathodic structure consisting of the platinum(100)-water-oxygen interface, for Proton Exchange Membrane Fuel Cells (PEMFCs). This approach aims to be integrated in a multiscale model [1], describing the kinetics in the cathodic electrode through density functional theory (DFT) and the macroscopic behavior through a pseudo 2D model for PEMFCs reported in previous works [1]. In the framework of MD simulations, it is required to define an interaction potential model that describes the size, the charge polarization and the chemical characteristics of the electrochemical interface. In this work TIP3P model is used to describe interaction among water molecules, whereas interaction among platinum, water and oxygen is modeled with Lennard-Jones 12-6 model including electrostatic interactions. MD simulations are performed in LAMMPS with a rigid wall of platinum and periodic boundary conditions in x and y directions, using a NPT ensemble to obtain the equilibrium configuration of the system at 1 bar and 353.15K The MD simulation allows to obtain the density distribution functions of water molecules and oxygen atoms perpendicular to X-Y plane. Then, the density distribution profiles are used to calculate the charge distribution through formal charge of water and oxygen. Finally the Poisson equation is employed to get the electrostatic potential across the interface and an associated electrostatic over-potential. Also several simulations are carried out at different cathodic current densities. The obtained water density distribution at OCV is validated according to the results of previous works [2-4]. [1] S. Castaneda Ramirez, a. E. Perez Mendoza, és R. E. Ribadeneira Paz, ECS Trans., 66, 19–39 (2015). [2] X. Xia, L. Perera, U. Essmann, és M. L. Berkowitz, Surf. Sci., 335, 401–415 (1995). [3] K. Foster, K. Raghavan, és M. Berkowitz, Chem. Phys. Lett., 162, 32–38 (1989). [4]E. Spohr, J. Phys. Chem., 93, 6171–6180 (1989). [5] K. Heizinger, Pure and appl Chem. 63, 1733-1742 (1991). [6] D. A. Rose, I. Benjamin. J. Phys. Chem 95 (1991).

Multi-Scale Modeling of Transports inside PEMFC By Combining Multi-Phase CFD Fuel Cell Model with Lattice Boltzmann Method

The objective of this work is to gain the mechanical understanding of the water management in the proton exchange membrane fuel cell (PEMFC). Water is a by-product of the fuel cell reaction and its amount is proportion to the current of fuel cell output. Water is used to retain the proper hydration level in the PEM. At the same time, condensed water in the flowfield and the gas diffusion layer (GDL) reduces oxygen transport to the oxygen reduction reaction (ORR) area. Therefore, excess accumulation of condensed water causes to lower the performance, particularly at the higher current densities. Detailed simulation of two-phase water in the GDL is significantly important to understand the water management.This work shows the successful in development of a multi-scale calculation technique that incorporates various scales of numerical model in a fuel cell and simultaneously performed a prediction. The outcomes of this work are, (i) development of two-phase fluid model in the micro-scale porous structure of GDL, and (ii) integration of this micro-scale GDL fluid model with a state-of-the-art macro-scale flowfield fluid model to predict two-phase water in the fuel cell. Figure 1 gives the concept of modeling approach at each component of the fuel cell. The flowfield in the bipolar plate and MEA models are calculated using traditional computational fluid dynamics (CFD) method with existing PEMFC model [1-3]. The two-phase fluid in the micro-scale porous structure of GDL is numerically predicted by Lattice Boltzmann Method (LBM) [4-5]. The solution of each iteration from CFD and LBM are required to simultaneously exchange for the next iteration until all solutions are converged, especially at the interfaces. In this figure, it shows the flowfield is transformed into the macro-scale CFD model and the image of detail structured GDL is converted into micro-scale LBM model. Actual porous structure imaging of GDL is obtained by the nano-scale high special resolution x-ray computed tomography. Figure 2 shows an example of the predictions from the simulation when the macroscopic flowfield model is combined with the microscopic GDL model while performing the calculation. The predictions give the detail distributions of variables in every components of the multiscale model. In this figure, the current density distribution on MEA surface, the liquid water transport inside the GDL, and the temperature of solid and fluid phases inside the GDL are presented.

Control of PEM fuel cell power system using sliding mode and super-twisting algorithms

Traditional sliding mode controller applied to a DC/DC boost converter for the improvement and optimization of the proton exchange membrane fuel cell (PEMFC) system efficiency, has the drawback of chattering phenomenon. Thus, based on the analysis of the mathematical model of PEMFC, this paper addresses the second order super twisting algorithm (STA) as a solution of chattering reduction, Stability of the closed loop system is analytically proved using Lyapunov approach for the proposed controller. The model and the controllers are implemented in the MATLAB and SIMULINK environment. A comparison of results indicates that the suggested approach has considerable advantages compared to the classical sliding mode control.

A study on scaled up proton exchange membrane fuel cell with various flow channels for optimizing power output by effective water management using numerical technique

Water management in a Proton Exchange Membrane Fuel Cell (PEMFC) is of great concern for effective cell performance. Existing studies for scaled up model of PEMFC are limited only to experimental work where effective water management with respect to flow channels are very few, time consuming and less economical. In this connection, an extensive numerical study is carried out for optimizing the flow channels with respect to optimal pressure drop and water management for the scaled up model (225 cm2) of PEMFC which is a novel approach in the field of PEMFC. This numerical study involves four different configurations of flow channels. In the first configuration, predominantly existing serpentine parallel flow channel for 25 cm2 is extended to 225 cm2 cross-sectional area. Serpentine zig-zag, straight parallel and straight zig-zag are the other three flow channels considered respectively in this study. The three dimensional flow through the PEMFC is simulated by solving the governing principles namely mass, momentum, energy, species and electro-chemical equations. It is found that the power density developed by straight flow channel with zig-zag flow path is 0.3758 W/cm2 and is the maximum of the configurations considered and this is due to effective water management with minimal pressure drop.

Gas diffusion layer properties on the performance of proton exchange membrane fuel cell: pc-s relationship with K-function

Accurate capillary pressure-liquid water saturation relationship (pc-s) plays a key role in predicting the performance of proton exchange membrane (PEM) fuel cells and the two-phase flow characteristics in gas diffusion layer (GDL). In this work, a validated Leverett function (K-function) based on the experimental pc-s data for SGL24 and SGL10 series carbon paper GDL materials is incorporated into a three-dimensional and two-phase PEM fuel cell model to investigate the effects of gas diffusion layer properties on the cell performance. Special emphasis is put on Polytetrafluoroethylene (PTFE) loading (5–20 wt%) in the GDL, compression pressure (1–4 MPa) and micro-porous layer (MPL). The results show that the cell exhibits better performance when a higher PTFE loading of 20% and a lower compression pressure of 1 MPa are adopted. However, liquid water is hard to drain from the GDL with the 5 wt% PTFE loading due to the low hydrophobicity, especially under the ribs; for the high compression pressure of 4 MPa, small effective porosity caused by the pressure becomes the major resistance of water drainage. The existence of MPL is also very helpful to reduce the water saturation in the GDL.

Simultaneous Optimization of Net Power and Enhancement of PEM Fuel Cell Lifespan Using Extremum Seeking and Sliding Mode Control Techniques

One of the challenges concerning proton exchange membrane fuel cell (PEMFC) is how to control the air compressor voltage so that enough oxygen is provided for reaction, while the net power (the produced electrical power minus the air compressor used power) is maximized. Another challenge is the enhancement of the PEMFC lifespan by controlling the inlet hydrogen flow in a way that enough hydrogen is provided for reaction, and the pressure difference between cathode and anode is kept as small as possible. This paper presents a gradient-based extremum seeking control, which controls the inlet oxygen flow for net-power optimization of a PEMFC. High speed, simplicity, and online control decision are the advantages of this controller. Additionally, the paper presents a first order sliding mode controller for decreasing the pressure difference between gases at cathode and anode in order to enhance the PEMFC lifespan. Control law simplicity, not requiring a state observer, and chatter free response are the advantages of the sliding mode controller, which controls the inlet hydrogen flow. Both controllers are simulated on a sample PEMFC model simultaneously, and the results show that the partial pressure difference of oxygen and hydrogen is approximately zero, and at the same time the PEMFC net power is increased up to 17 percent.

Modeling and optimization for proton exchange membrane fuel cell stack using aging and challenging P systems based optimization algorithm

Accurate models of PEM (proton exchange membrane) fuel cells are of great significance for the analysis and the control for power generation. We present a new semi-empirical model to predict the voltage outputs of PEM fuel cell stacks. We also introduce a new estimation method, called AC-POA (aging and challenging P systems based optimization algorithm) allowing deriving the parameters of the semi-empirical model. In our model, the cathode inlet pressure is selected as an additional factor to modify the expression of concentration over-voltage Vcon for traditional Amphlett's PEM fuel cell model. In AC-POA, the aging-mechanism inspired object updating rule is merged in existing P system. We validate through experiments the effectiveness of AC-POA and the fitting accuracy of our model. Modeling comparison results show that the predictions of our model are the best in terms of fitting to actual sample data.

Modeling of commercial proton exchange membrane fuel cell using support vector machine

A method for predicting the performance of a proton exchange membrane fuel cell (PEMFC) system of a commercially available electrical bicycle using a support vector machine (SVM) is presented in this paper. The main advantage of the results obtained from this study is facilitating the use of carbon-free fuels instead of carbon-based ones and consequently reducing the energy consumption. Because such cells are nonlinear, multivariable systems that are difficult to model through traditional methods hence SVMs, which are powerful tools for predicting PEMFC performance, are used. Experimental data obtained from a 250 W PEMFC were used to predict parameters to describe the V–I, P–I, and efficiency–power curves, and then, the data was applied to predict overall PEMFC performance. To evaluate the functionality of suggested model, this method has been compared with multi-layer perceptron (MLP) artificial neural network model. It has been demonstrated that, the error of SVM model is much smaller than MLP, and the proposed approach has better performance to predict the PEM fuel cell curve for the electrical bicycle. It was shown that the coefficient of determination in the SVM prediction model for power–current curve is approximately 99%, which is 97% for MLP model that makes the proposed black box SVM PEMFC model suitable for monitoring and simulating fuel cell performance in the electrical bicycle that is beneficial for its variety of energy saving applications.

A numerical analysis on the effect of different architectures of membrane, CL and GDL layers on the power and reactant transportation in the square tubular PEMFC

In this paper a numerical analysis was applied to evaluate performance of square tubular Proton Exchange Membrane (PEM) with three different architectures of catalyst (CL), membrane and gas diffusion layer (GDL). Three different cases were investigated for cathode and anode which are square peripheral (SP), square chordal (SC) and square bisectors (SB). Commercial computational fluid dynamic code (CFD) was employed for solving conservative form of continuity and momentum, species transportation and energy equations. The obtained polarity curve was validated with experimental data for base model and then, this curve and the related power density was compared with conventional base PEM fuel cell model. The results indicated that all of the three square tubular architectures with different layers have better performance compared to base model and higher current densities could be achieved via these architectures. Among the three mentioned cases, SC had the highest current density and power density compared to SP and SB cases. SC had also higher hydrogen and oxygen consumption compared to two other cases because of uniform reaction in allover the area and elimination of regions in which the reaction is slow (i.e. Dead zone). The results showed the amount of hydrogen consumption at the cathode along the channel for SP, SC, SB cases 63.8%, 94% and 79.16% respectively, relative to input hydrogen amounts. Also, comparison of water concentration values for three SP, SC and SB cases showed 35.6%, 49.5% and 43.57% of inlet values respectively. This confirms that reaction taken place in SC is maximum. This research proves that, higher power densities could be achieved by employing different geometries and different arrangement of layers, which could considerably reduce the cost while improving efficiency of tubular PEM's.

Dynamic modelling of PEM fuel cell of power electric bicycle system

Fuel cells eliminate pollution caused by burning fossil fuels; hence, a proton exchange membrane fuel cell (PEMFC) is one of the promising technological advances for the future of the transportation industry. The key existing challenges for fuel cell commercialization are performance, design and vehicle efficiency. Since the analytical model expressing fuel cells' characteristics is not accurate in comparison with the real system's performance a robust and dynamic model for fuel cells is of great importance. This study aims to introduce an optimized model for PEMFC using an electric bicycle that consists of a 250 W fuel cell, battery pack, DC/DC convertor, electric motor and electric control unit (ECU). In the first phase of this multi-fold study, the analytical model of PEMFC's efficiency has been compared with the experimental results obtained from the electric bicycle. The result of this phase showed an overall system efficiency of 35.4% and a maximum fuel cell efficiency of 63%. This confirms that fuel cell performance is least efficient when functioning under maximum output power conditions. In the second phase of this research, the collected data was used for developing linear and nonlinear regression models. The resulting model was compared with an artificial neural network used for the same purpose, and their prediction efficiencies compared. Results show that neural network modelling improves accuracy and provides promising performance for the electric bicycle system.

Effect of humidity content and direction of the flow of reactant gases on water management in the 4-serpentine and 1-serpentine flow channel in a PEM (proton exchange membrane) fuel cell

The performance of a PEM (proton exchange membrane) fuel cell depends on design and operating parameters such as relative humidity, operation pressure, and number of channels and direction of the flow of reactant gases. In this study, a three-dimensional, two-phase model has been established to investigate the water management and performance of PEM fuel cell with rectangular geometry and 1-serpentine and 4-serpentine with parallel flow, counter flow and cross flow for hydrogen and oxygen. The numerical simulation was realized with a PEM fuel cell model based on the FLUENT. The active area of each cell is 24.8 cm2 that its weight is 1300 gr. The material of the gas diffusion layer is carbon clothes, the membrane is nafion117 and the catalyst layer is a plane with 0.004 g cm−2 platinum. Pure hydrogen is used on the anode side and oxygen on the cathode side. Simulation results are obtained for voltage as a function of current density at different humidity. The simulation results are compared with the experimental data, and the agreement is found to be good. The results show that the cell performance at lower voltages increases with increasing humidity in cell with 4-Serpentine flow channel and also in cell with 1-Serpentine flow channel, cell performance at all voltages increases with increasing humidity. In cell with 4-Serpentine and parallel flow channel cell performance is better than counter and cross flow in low voltage and in cell with 1-Serpentine and parallel flow, performance is better than counter and cross flow in high voltage.

Effect of the pore size variation in the substrate of the gas diffusion layer on water management and fuel cell performance

The gas diffusion layer (GDL) is a key component of a proton exchange membrane (PEM) fuel cell due to its role as a pathway for fuel, air, and water. GDL determines the mass balance and water management in the PEM fuel cell. Thus, an investigation of the optimal structural characteristics of the GDL with improved water management is important to ensure high performance of the PEM fuel cell. In this study, a PEM fuel cell model that considers the structural characteristics of GDL is developed, and the various the GDL structural characteristics are analyzed and validated. Specifically, the effects of pore size variation in the substrate of the GDL on water management and cell performance are investigated. Two GDL samples with different pore sizes are evaluated according to the porosity, pore size, thickness, and internal contact angle to understand the basic structural characteristics of the GDL. The GDL structural parameters with the basic characteristics are incorporated into the developed model. The cell performance is predicted to be relative to the two-phase mass transport inside the GDL. The characteristics of the micro-porous layer (MPL) and MPL penetration part are found to be affected by the variation in the macro-pore size of the substrate. The water management capability of the GDL varies with these differences with respect to water retention and removal characteristics. Under the condition of relative humidity (RH) 100%, the averaged saturation value of the MPL and MPL penetration part of the GDL with small macro-pore in the substrate is 18.8% higher than that of the GDL with large macro-pore in the substrate. The cell performance is also affected by the operating conditions of relative humidity and current load. The voltage of the GDL with small macro-pore in the substrate at the current density of 1.6A/cm2 is 10.3% lower than that of the GDL with large macro-pore in the substrate under RH 100%.

Optimization of Flow Channel Design and Operating Parameters on Proton Exchange Membrane Fuel Cell Using MATLAB

Operating parameters like pressure, temperature, the stoichiometric ratio of reactants, relative humidity and design parameters like rib width to channel width (L:C), the shape of the flow channel and the number of passes on the flow channel are influencing the performance of the Proton Exchange Membrane Fuel Cell (PEMFC). In this paper, optimization of operating and design parameters such as pressure, temperature, inlet reactant mass flow rate and various rib width to channel width (L:C) 1:1, 1:2, 2:1 and 2:2 on serpentine and interdigitated flow channel of 25cm2 active area of the PEMFC was considered. Creo Parametric 1.0 and CFD Fluent 14.0 software packages were used to create the 3 Dimensional (3- D) model and simulation of PEMFC. The optimization was carried out on the various parameters with MINITAB 17 software and MATLAB software. From the first stage, the Landing to channel width (L: C) - 1:1 of serpentine and the interdigitated flow channel has the maximum influence on fuel cell performance and square of response factor (R2) was achieved from the Taguchi method by MINITAB 17 software as 99.48 and 99.71 % respectively. In the second stage, the regression equation or mathematical model obtained from MINITAB 17 software were fed into the MATLAB software to get optimized parameters. Further the power densities were obtained corresponding to the optimized parameters using the CFD Fluent 14.0 software.