[en] 'Full text:' In February 2005, Ballard announced its most recent advances in PEMFC stack technology. This technology development exhibited, we believe, for the first time the capability of a single PEMFC stack design to demonstrate combined excellence in cost reduction, freeze start capability from -20 C and durability under an automotive OEM defined dynamic operating cycle, comparable to that experienced by a fuel cell stack in an actual vehicle. One month later, building on the above technology leadership demonstration, Ballard announced a technology ^'oad map' that defined a path to commercially viability for a PEMFC stack by 2010. The key target parameters for cost reduction, durability, freeze start and stack power density are described in detail along with demonstrated historical capability and a clear path as to how Ballard will achieve the required targets. (author)

[en] Bipolar plate for Proton Exchange Membrane (PEM) fuel cell was fabricated with various materials and characterized by different techniques. Two types of gas flow fields, serpentine and parallel, were designed for bipolar plates and their effect on the functioning of fuel cells was investigated. Pressure drop between the two designs, at inlet and outlet of gases was different and its effect was reported. In the fabrication process of membrane electrode assemblies (MEA), the platinum catalyst was synthesized in the laboratory and this catalyst was deposited on the Nafion membrane with the help of ionomer emulsion. Then gas diffusion layers were placed on both sides of the membrane. Different MEAs versions (imported and indigenous) were assembled and tested in the fuel cells and their efficiency was evaluated in terms of current, voltage and power, A fuel cell test stand was developed to operate and test the working of single cell and fuel cell stack is also described. Polarization curves were drawn to evaluate the performance of fuel cells. These studies are directed at the development of different fuel cell components which are tested under the same conditions for comparison. (author)

[en] 'Full text:' Mathematical modeling is an important tool for PEM fuel cell commercialization. Mathematical models can illustrate the effect of the different processes on the overall performance of a PEM fuel cell; thus, mathematical models can be used to as a design tool to find optimal designs and operating conditions. A general formulation for a comprehensive fuel cell model, based on the conservation principle and volume-averaging, is presented. The model formulation includes the electro-chemical reactions, proton migration, and the mass transport of the gaseous reactants and liquid water. Additionally, the model formulation can be applied to all regions of the PEM fuel cell: the bipolar plates, gas flow channels, electrode backing, catalyst, and polymer electrolyte layers. Numerical results, showing the effect of water flooding on PEM fuel cell performance, are presented. (author)

[en] This paper addresses the importance of the boundary conditions for the charge conservation equation in the modeling of fuel cells. In this context, we analyze the charge transport in an electric conductor, aiming to determine whether constant current and constant potential boundary conditions can be interchanged without disturbing the local current density distribution in the cell. Their interchangeability can be described with a dimensionless number, referred to as the “interchangeability number”, which captures the relevant operating, geometrical and material parameters. The effect of the interchangeability number is further explored in a model for non-isothermal two-phase flow in a proton exchange membrane fuel cell, for which is it verified that the interchangeability number should be much less than 3, in order to ensure that the prediction for the local current density distribution at the catalyst layers remains the same regardless of galvanostatic or potentiostatic boundary conditions

[en] This study deals with the thermodynamic modeling of a polymer electrolyte membrane (PEM) fuel cell power system for transportation applications. The PEM fuel cell performance model developed previously by two of the authors is incorporated into the present model. The analysis includes the operation of all the components in the system, which consists of two major modules: PEM fuel cell stack module and system module and a cooling pump. System module includes air compressor, heat exchanger, humidifier and a cooling loop. A parametric study is performed to examine the effect of varying operating conditions (e.g., temperature pressure and air stoichiometry) on the energy and exergy efficiencies of the system. Further, thermodynamic irreversibilities in each component of the system are determined. It is found that, with the increase of external load (current density), the difference between the gross stack power and net system power increases. The largest irreversibility rate occurs in the fuel cell stack. Thus, minimization of irreversibility rate in the fuel cell stack is essential to enhance the performance of the system, which in turn reduces the cost and helps in commercialization of fuel cell power system in transportation applications. (author)

[en] Fuel cells are electrochemical energy converters. They convert the chemical energy contained in the fuel into electricity while producing water and heat. Compared to the traditional energy converters, such as batteries and internal combustion engines, fuel cells are marked by high conversion efficiency and very low emissions.This work contains a computer study of optimization and control of fuel cells systems. An analytical study of the fuel (Hydrogen and air) supply system was performed taking into account compressor, cooling and humidification subsystems. In addition, the stack system, which consists of a lot of cells, was analyzed using the experimental equations of Nafion 117 membrane. The model of the whole system was then implemented in MATLAB/Simulink environment. The effect of the cathode pressure and the membrane water content on the polarization curves of the cell was examined. To validate the model, the responses of the model to step changes in the compressor voltage and the current drawn from the stack, were used. More attention was given to the net power which can be provided by the system, taking into account the power wasted by the compressor. (author)

[en] This paper presents a model of the Proton Exchange Membrane Fuel Cell (PEMFC) suitable for system simulation and optimisations using physically meaningful parameters. It is capable of modelling the transient behaviour and distributed nature of the cell. The model of the PEMFC is built up using discrete model elements representing subcomponents of the cell. Built in PSPICE, MATLAB/Simulink and VTB, the proposed model closely follows the physical layout of the actual cell. The interactions of chemical reactants, products and the main electrical circuit are represented in an electrochemically and physically accurate manner. The interactions include those of the water and protons, electrode-electrolyte charge double layer, reactant diffusion induced voltage drops and cross-over currents. Results are given for steady-state and transient operation and compared to experimental results. Conclusions are drawn concerning the ease of use of the model. (author)

[en] In this paper, an innovative robust prediction algorithm for performance degradation of proton exchange membrane fuel cell (PEMFC) is proposed based on a combination of model-based and data-driven prognostic method. A novel approach using the moving window method is applied, in order to 1) train the developed models; 2) update the weight factors of each method and 3) further fuse the predicted results iteratively. In the proposed approach, both model-based and data-driven methods are simultaneously used to achieve a better accuracy. During the prediction process, each dataset in the proposed moving window are divided into three sections respectively: training, evaluation and prediction. The training data are used first to identify the models parameters. The evaluation data are then used to measure the weight of each method, which represents the degree of confidence of each method in the actual state. Based on these dynamically adjusting weight factors, the prediction results from different methods are then fused using weighted average methodology to calculate the final prediction results. In order to verify the proposed method, three experimental validations with different aging testing profiles have been performed. The results demonstrate that the proposed hybrid prognostic approach can achieve a higher accuracy than conventional prediction methods. In addition, in order to find the satisfactory trade-off between the prediction accuracy and forecast time for optimizing on-line prognostic, the performance variation of proposed approach with different moving window length is further showed and discussed. - Highlights: • Long-term aging trend of PEMFC is captured by a degradation empirical model. • Nonlinear characteristics of PEMFC degradation are predicted by a NARNN model. • Both model-based and data-driven prognostic approaches are simultaneously used. • Moving window method iteratively updates the prediction process. • Performance variation of hybrid prognostic with different prediction horizon is shown.

[en] The performance of a polymer electrolyte membrane (PEM) fuel cell stack consisting 51 cells has been analyzed using a flow network model incorporating the minor losses. The distributions of pressure, molar flow rate and concentration for the fuel and oxidant streams in the stack are determined. The distributions are used in the single cell model developed previously to evaluate the stack voltage and the cell-to-cell voltage distributions. Analysis has been carried out for a variety of flow configurations and bipolar plate designs. It was found that the minor losses increase the stack operating pressure and the power requirement for oxidant supply and change the cell-to-cell voltage variations in the stack. A symmetric double inlet-single outlet topology provides optimal stack performance with reasonably low compressor power requirement for the reactant flow and minimum cell-to-cell voltage variations. The stack performance is considerably affected by the size and the number of flow channels on bipolar plate. (author)

[en] Fuel cells have gained considerable interest as a means to efficiently convert the energy stored in gases like hydrogen and methane into electricity. Further developing fuel cells in order to reach cost, safety and reliability levels at which their widespread use becomes feasible is an essential prerequisite for the potential establishment of a 'hydrogen economy'. A major factor currently obviating the extensive use of fuel cells is their relatively high costs. At present we estimate these at about 1100 EUR(2005)W for an 80 kW fuel cell system but notice that specific costs vary markedly with fuel cell system power capacity. We analyze past fuel cell cost reductions for both individual manufacturers and the global market. We determine learning curves, with fairly high uncertainty ranges, for three different types of fuel cell technology - AFC, PAFC and PEMFC - each manufactured by a different producer. For PEMFC technology we also calculate a global learning curve, characterised by a learning rate of 21% with an error margin of 4%. Given their respective uncertainties, this global learning rate value is in agreement with those we find for different manufacturers. In contrast to some other new energy technologies, R and D still plays a major role in today's fuel cell improvement process and hence probably explains a substantial part of our observed cost reductions. The remaining share of these cost reductions derives from learning-by-doing proper. Since learning-by-doing usually involves a learning rate of typically 20%, the residual value for pure learning we find for fuel cells is relatively low. In an ideal scenario for fuel cell technology we estimate a bottom-line for specific (80 kW system) manufacturing costs of 95 EUR(2005)W. Although learning curves observed in the past constitute no guarantee for sustained cost reductions in the future, when we assume global total learning at the pace calculated here as the only cost reduction mechanism, this ultimate cost figure is reached after a large-scale deployment about 10 times doubled with respect to the cumulative installed fuel cell capacity to date. (author)