A multi-objective optimisation model for a general polymer electrolyte membrane fuel cell system

This paper presents an optimisation model for a general polymer electrolyte membrane (PEM) fuel cell system Suitable for efficiency and size trade-offs investigation. Simulation of the model for a base case shows that for a given output power, a more efficient system is bigger and vice versa. Using the weighting method to perform a multi-objective optimisation, the Pareto sets were generated for different stack output powers. A Pareto set, presented as a plot of the optimal efficiency and area of the membrane electrode assembly (MEA), gives a quantitative description of the compromise between efficiency and size. Overall, our results indicate that, to make the most of the size-efficiency trade-off behaviour, the system must be operated at an efficiency of at least 40% but not more than 47%. Furthermore, the MEA area should be at least 3 cm(2) W-1 for the efficiency to be practically useful. Subject to the constraints imposed on the model, which are based on technical practicalities, a PEM fuel cell system such as the one presented in this work cannot operate at an efficiency above 54%. The results of this work, specifically the multi-objective model, will form a useful and practical basis for subsequent techno-economic studies for specific applications. (C) 2009 Elsevier B.V. All rights reserved

PEMFC performance improvement through oxygen starvation prevention, modeling, and diagnosis of hydrogen leakage

Catalyst degradation results in emerging pinholes in Proton Exchange Membrane Fuel Cells (PEMFCs) and subsequently hydrogen leakage. Oxygen starvation resulting from hydrogen leaks is one of the primary life-limiting factors in PEMFCs. Voltage reduces as a result of oxygen starvation, and the cell performance deteriorates. Starved PEMFCs also work as a hydrogen pump, increasing the amount of hydrogen on the cathode side, resulting in hydrogen emissions. Therefore, it is important to delay the occurrence of oxygen starvation within the Membrane Electrode Assembly (MEA) while simultaneously be able to diagnose the hydrogen crossover through the pinholes. In this work, first, we focus on catalyst configuration as a novel method to prevent oxygen starvation and catalyst degradation. It is hypothesized that the redistribution of the platinum catalyst can increase the maximum current density and prevent oxygen starvation and catalyst degradation. Therefore, a multi-objective optimization problem is defined to maximize fuel cell efficiency and to prevent oxygen starvation in the PEMFC. Results indicate that the maximum current density rises about eight percent, while the maximum PEMFC power density increases by twelve percent. In the next step, a previously developed pseudo two-dimensional model is used to simulate fuel cell behavior in the normal and the starvation mode. This model is developed further to capture the effect of the hydrogen pumping phenomenon and to measure the amount of hydrogen in the outlet of the cathode channel. The results obtained from the model are compared with the experimental data, and validation shows that the proposed model is fast and precise. Next, Machine Learning (ML) estimators are used to first detect whether there is a hydrogen crossover in the fuel cell and second to capture the amount of hydrogen cross over. K Nearest Neighbour (KNN) and Artificial Neural Network (ANN) estimators are chosen for leakage detection and classification. Eventually, a pair of ANN classifier-regressor is chosen to first isolate leaky PEMFCs and then quantify the amount of leakage. The classifier and regressor are both trained on the datasets that are generated by the pseudo two-dimensional model. Different performance indexes are evaluated to assure that the model is not underfitting/overfitting. This ML diagnosis algorithm can be employed as an onboard diagnosis system that can be used to detect and possibly prevent cell reversal failures

Three-dimensional numerical study of proton exchange membrane fuel cell design

Performance of proton exchange membrane (PEM) fuel cells is dependent of a set of complex physical and chemical processes occurring simultaneously. Bipolar plates are important components of PEM fuel cells because they are the first stage of the flow distribution system. A non-uniform flow distribution across the active reaction area within PEM fuel cells will probably lead to an unbalanced use of the precious catalyst, and a lower overall efficiency of the device than expected. A three-dimensional numerical model has been developed to evaluate the PEM fuel cell including the current collectors, flow channels, gas diffusion layers, and membrane. This model takes into account the multi-component fluid flow in porous medium, electrochemical kinetics and water transport across membrane by electro-osmosis, diffusion and convection. Different fuel cell design cases, associated with their own bipolar plate designs, have been studied. Numerical results from the developed model show that the predicted polarization curve is in very good agreement with the experimental data. Results also show that the fluid flow distribution in the baseline design is very non-uniform, which is not favorable for the use of catalyst and the high efficiency fuel cell. In order to improve the fuel cell efficiency, the bipolar plate design has been optimized, which then greatly increases the current density or power of fuel cell under the same operating conditions compared with the baseline design. Parametric study of the fuel flow rate on the current density has also been performed. Results reveal that the flow rate of fuel or air greatly influences the water content distribution within the proton exchange membrane, thus significantly impacting the performance of the PEM fuel cell. Generally, uniform fluid flow inside the entire plates and the proper humidity of the fuel cell are significantly important to the high performance PEM fuel cell

MODELLING AND FAULT DIAGNOSIS APPROACH FOR PROTON EXCHANGE MEMBRANE FUEL CELL SYSTEMS INCORPORATING AMBIENT CONDITIONS

Proton exchange membrane fuel cell (PEMFC), as a source of electrical power, provides numerous benefits such as zero carbon emission and high reliability as compared to wind and solar energy. PEMFC operates at very low temperature, high power density, and has very high durability as compared to other fuel cells. Being a non-linear power source with high sensitivity to ambient conditions variation, the prediction of PEMFC voltage and temperature is a complicated issue. The most common PEMFC models are classified as mechanistic models, semi-empirical models, and purely empirical methods. The mechanistic models are complex and require differential equations to predict the voltage and temperature of PEMFC. However, the semi-empirical models are less complicated and can be used easily for the online prediction of PEMFC outputs. Therefore, the first part of this thesis attempt to model the voltage of PEMFC using simple and effective semi-empirical equations. The initial feature of the proposed technique is to incorporate the features of a mechanistic model with less complex equations. The model considers the internal currents and the internal voltage drop associated with the PEMFC. Besides, activation and concentration voltage drops are addressed based on theoretical functions. Thus, the proposed model provides an additional benefit that not only does the output voltage model satisfy the voltage for both loaded and unloaded conditions but also the component voltage drops waveforms match with the theoretical waveforms given in the mechanistic models. The second part of the thesis focuses on modelling the PEMFC temperature. Previously most temperature models use complex equations incorporating PEMFC output voltage which is not a good option as the temperature must be predicted using only load current and ambient temperature. The model proposed in this thesis is developed through an algorithm that tracks the online changes in the load current and ambient temperature. It provides the accurate temperature of PEMFC by using a simple first-order equation with the help of a tracking algorithm. Quantum lig tening search algorithm (QLSA) is used for the optimization of constant parameters for both voltage and temperature models. The PEMFC performance is affected by factors such as variations in ambient temperature, pressure, and air relative humidity and thus they are vital for predicting PEMFC performance. The thesis also attempts to directly predict the variations in PEMFC voltage under varying ambient conditions at different load resistance. For this purpose, statistical analysis is used to propose empirical equations that can predict the variations in PEMFC voltage for varying ambient conditions. In this context of the model development, the parameters which are significantly varying with ambient changes are identified with the help of statistical regression analysis and represented as ambient temperature and air relative humidity dependent parameters. The enhanced semi-empirical voltage model is verified by performing experiments on both the Horizon and NEXA PEMFC systems under different conditions of ambient temperature and relative humidity with root mean square error (RMSE) less than 0.5. Results obtained using the enhanced model are found to closely approximate those obtained using PEMFCs under various operating conditions, and in both cases, the PEMFC voltage is observed to vary with changes in the ambient and load conditions. Inherent advantages of the proposed PEMFC model include its ability to determine membrane-water content and water pressure inside PEMFCs. The membrane-water content provides clear indications regarding the occurrence of drying and flooding faults. For normal conditions, this membrane water content ranges between 12.5 to 6.5 for the Horizon PEMFC system. Based on simulation results, a threshold membrane water- content level is suggested as a possible indicator of fault occurrence under extreme ambient conditions. Limits of the said threshold are observed to be useful for fault diagnosis within the PEMFC systems

Real-Time Implementation of a New MPPT Control Method for a DC-DC Boost Converter Used in a PEM Fuel Cell Power System

settings Open AccessArticle Real-Time Implementation of a New MPPT Control Method for a DC-DC Boost Converter Used in a PEM Fuel Cell Power System by Mohamed Derbeli 1,2,* [OrcID] , Oscar Barambones 1 [OrcID] , Mohammed Yousri Silaa 1 [OrcID] and Cristian Napole 1 [OrcID] 1 Engineering School of Vitoria, University of the Basque Country UPV/EHU, Nieves Cano 12, 1006 Vitoria, Spain 2 National Engineering School of Gabes, University of Gabes, Omar Ibn-Elkhattab, 6029 Gabes, Tunisia * Author to whom correspondence should be addressed. Actuators 2020, 9(4), 105; https://doi.org/10.3390/act9040105 Received: 30 August 2020 / Revised: 25 September 2020 / Accepted: 10 October 2020 / Published: 16 October 2020 (This article belongs to the Section High Torque/Power Density Actuators) Download PDF Browse Figures Abstract Polymer electrolyte membrane (PEM) fuel cells demonstrate potential as a comprehensive and general alternative to fossil fuel. They are also considered to be the energy source of the twenty-first century. However, fuel cell systems have non-linear output characteristics because of their input variations, which causes a significant loss in the overall system output. Thus, aiming to optimize their outputs, fuel cells are usually coupled with a controlled electronic actuator (DC-DC boost converter) that offers highly regulated output voltage. High-order sliding mode (HOSM) control has been effectively used for power electronic converters due to its high tracking accuracy, design simplicity, and robustness. Therefore, this paper proposes a novel maximum power point tracking (MPPT) method based on a combination of reference current estimator (RCE) and high-order prescribed convergence law (HO-PCL) for a PEM fuel cell power system. The proposed MPPT method is implemented practically on a hardware 360W FC-42/HLC evaluation kit. The obtained experimental results demonstrate the success of the proposed method in extracting the maximum power from the fuel cell with high tracking performance.This work was partially supported by Eusko Jaurlaritza/Gobierno Vasco [grant number SMAR3NAK ELKARTEK KK-2019/00051]; the Provincial Council of Alava (DFA) [grant number CONAVAUTIN 2] (Collaboration Agreement)

Mass transport in polymer electrolyte membrane fuel cells using natural convection for air supply

A fuel cell converts chemical energy into electricity and heat through electrochemical reactions. Polymer electrolyte membrane fuel cells (PEMFCs) are approaching commercialization in many applications, including transportation, stationary power, and portable devices. In this thesis, the focus was on small-scale PEMFCs, in which natural convection is used as the air supply method. A cell design with straight vertical cathode channels was studied using experimental and modeling methods, in order to obtain a quantitative insight into mass transport phenomena and to identify the performance limiting processes. The variation of mass transport conditions over the active area of the cell was studied using a current distribution measurement system, which was based on the use of a segmented current collector. The accuracy of the method was analyzed by experimental work and numerical simulation. In order to quantify the local mole fractions of water and oxygen, and the velocity of buoyancy-driven air flow in the cathode channel, a numerical model was developed to describe mass transport in the cathode channel and the gas diffusion layer. Water transport across the polymer membrane was studied by measuring the fraction of product water exiting through the anode. The results give indication of the variation of net water transport coefficient across the active area. The redistribution of water along with the hydrogen flow was also observed. The effect of ambient temperature and relative humidity on cell performance was investigated in a climate chamber. For stack research, a measurement approach was developed for determining the ohmic voltage losses of individual cells in a stack by the current interruption method. As an overall conclusion, it was found that the cell design should be improved especially from the point of view of water management. In order to reduce flooding problems, the cross-section and length of the cathode channels were identified as key parameters to be optimized. It was also found that mechanically rigid gas diffusion layer materials are advantageous for designing an optimized geometry. In addition, it was found that the choice of the anode flow geometry can be used to control the distribution of water across the active area.reviewe

Development of in-plane models for the analysis of dead-ended and anode bleeding operation modes and the cell degradation with carbon corrosion

Low durability and high cost are main drawbacks against commercialization of the proton exchange membrane fuel cell (PEMFC). The anode-bleeding (AB) operation mode offers a very high hydrogen utilization and cost reduction by eliminating additional components for the recovery of hydrogen in the flow-through mode and avoids the carbon corrosion reaction (CCR), which causes degradation of the catalyst layer and occurs typically when the bleeding rate is set to zero in the dead-ended (DEA) mode. Three-dimensional (3D) models are necessary for the analysis of PEMFCs. However, computational cost of 3D models is extremely high because of the strong nonlinearity due to complex interactions in the cell. In this dissertation, a pseudo-three-dimensional (P3D) two-phase and non-isothermal model is developed to reduce the computational cost and predict the cell performance with high accuracy. Results demonstrate that the P3D model results compare very well with ones from 3D model and experimental data from the literature. The P3D model is used to investigate the effects of geometric and operation parameters on the cell performance under DEA and AB operation modes. Moreover, the bleeding rate is optimized to sustain a stable transient cell voltage without the CCR in the cathode catalyst layer (CCL) while hydrogen utilization is kept at more than 99%. Furthermore, effects of the anode flow field design on the cell performance under the AB operation mode are investigated. Lastly, the P3D model is used to study effects of cell degradation on transport properties of the CC