Hydrogen consumption minimization method based on the online identification for multi-stack PEMFCs system

The proton exchange membrane fuel cell (PEMFC) stacks are not widely used in the field of transportation industry, due to their limited power. Thus, the PEMFC stacks usually connected in parallel or series to meet the load demand power in high-power applications. The hydrogen consumption of multi-stack fuel cells (MFCs) system is related to the efficiency and output power. In addition, the efficiency of PEMFC depends on the applied voltage and other parameters. Consequently, the hydrogen consumption of system changes with varying load, because the system parameters are also varying. It makes reducing the fuel consumption of system a challenging assignment. In order to achieve the goal of minimizing fuel consumption of parallel-connected PEMFCs system, this paper proposes a novel power distribution strategy based on forgetting factor recursive least square (FFRLS) online identification. The FFRLS algorithm is based on data-driven and uses real-time data of the system to improve the estimation accuracy of PEMFC system parameters. On the test bench of parallel-connected PEMFCs system consists of two 300 W PEMFC stacks, PEMFC stack controller, DC/DC converters, and DSP controller etc., a multi-index performance test and comparative analysis are carried out. The results showed that, the performance of proposed power allocation strategy has been successfully validated. In addition, compared with the power average and daisy chain algorithms, the proposed online identification power distribution method can get more satisfactory results. Such as, reducing the hydrogen consumption and improving efficiency.     

Optimal operating conditions to maximize the net power of polymer electrolyte membrane fuel cells: The stack-system interface of a commercial 18 kW module

A new, experimental method based on air flow rate rather than current is presented to optimize operating parameters for the stacks and systems of proton exchange membrane fuel cells (PEMFCs) for maximizing their net power. This approach is illustrated for a commercial 18 kW PEMFC module. The impact of contamination pressure drop across the cathode air filter is also investigated on the compressor behavior. It is further shown that a 4V reduction in the compressor voltage reduces its power consumption by 9.1%. Using the 3D graphs of the power-pressure-flow data, it is found that the stack pressure of 180 kPaa is superior to the higher tested pressures as it enhances the net power by 7.0 and 13.7% at different conditions. Application of the present study will lead to the development of PEMFCs with higher power output by optimizing stack pressure, stoichiometry and air flow to properly deliver the system design specifications.     

An efficient heap-based optimization algorithm for parameters identification of proton exchange membrane fuel cells model: Analysis and case studies

Proton Exchange Membrane fuel cells (PEMFCs) are a promising renewable energy source to convert the chemical reactions between hydrogen and oxygen into electricity. To simulate, evaluate, manage, and optimize PEMFCs, an accurate mathematical model is essential. Therefore, this paper improves the accuracy of a mathematical model for the PEMFC based on semi-empirical equations by proposing a meta-heuristic technique to optimize its unidentified parameters. Because the I–V characteristic curve of the PEMFC systems has a nonlinear and multivariable nature, conventional optimization techniques are difficult and time-consuming but modern meta-heuristic algorithms are ideally suited. Therefore, in this paper, a new improved optimization algorithm based on the Heap-based optimizer (HBO) has been proposed to estimate the unknown parameters of PEMFCs models using an objective function that minimizes the error between the measured and estimated data. This improved HBO (IHBO) effectively uses two strategies: ranking-based position update (RPU) and Lévy-based exploitation improvement (LEI) to improve the final accuracy to the SSE value with higher convergence speed. Four well-known commercial PEMFCs, (the 500 W BCS stack, NetStack PS6, H-12 stack, and AVISTA SR-12 500 W modular) are utilized to verify the proposed IHBO and compare it with 11 popular optimizers using various performance metrics. The experimental findings show the superiority of IHBO in terms of convergence speed, stability, and final accuracy, where IHBO could fulfill fitness values of 0.01170, 2.14570, 0.11802, and 0.00014 for the 500 W BCS stack, NetStack PS6, H-12 stack, and AVISTA SR-12 500 W modular, respectively.     

Effective methodology based on neural network optimizer for extracting model parameters of PEM fuel cells

I/V polarization curves of proton‐exchange membrane fuel cells (PEMFCs) are used to characterize the performance of single cells and stacks. Numerous semi‐empirical models are presented to predict such polarization curves by determining the unknown parameters of mathematical model of the PEMFCs stack. In this paper, a novel optimization approach, namely neural network algorithm (NNA) is applied for an estimation of the unknown PEMFC model parameters. The NNA is employed to minimize adopted objective function, which is formulated as the sum of squared deviations (SSD) between the actual data and estimated voltage points subjects to set of inequality constraints are satisfied. Three commercial types of PEMFCs stack namely Ballard Mark V, BCS‐500 W, and Nedstack PS6 are numerically simulated to show the effectiveness of the proposed NNA‐based tool for parameter identification. The minimum values of SSD are 0.8536 V ² for Ballard Mark V, 0.011698 V ² for BCS‐500 W stack, and 2.14487 V ² for Nedstack PS6, respectively. The obtained results of the NNA are compared with other optimizers recently published in the literature such as flower pollination algorithm, slap swarm optimizer, grey wolf algorithm, grasshopper optimization algorithm, and shark smell algorithm under the same conditions. The comparisons and other performance tests indicate the robustness and the competition of the adopted NNA‐based method for producing accurate I/V polarization curves under different operating scenarios.     

Optimal parameter identification of PEMFC stacks using Adaptive Sparrow Search Algorithm

In this paper, a new optimization algorithm called Adaptive Sparrow Search Algorithm (ASSA) is proposed for optimal model parameters identification of the proton exchange membrane fuel cell (PEMFC) stacks. The proposed ASSA is utilized for minimizing the sum of squared error (SSE) between the empirical stack voltage and the calculated stack voltage by optimal selection of the mentioned parameters in the PEMFC stack. The method is then performed to three case studies including Ballard Mark V, Horizon H-12, and NedStack PS6 under different operating conditions and give 0.82, 5.14, and 0.097 of SEE which is the least value for all three case studies. The results of the algorithm are compared with some reported works in the literature including CGOA, GRA, and basic SSA to show the method prominence. The final results indicated that the proposed ASSA has the best efficiency toward the others.     

The durability investigation of a 10‐cell metal bipolar plate proton exchange membrane fuel cell stack

The metal bipolar plates (BPs) have replaced the graphite BPs in vehicle‐used proton exchange membrane fuel cell (PEMFC) stack because of their high volume power density. To investigate the durability of metal BP stack, this paper performed a durability test of 2000 hours on a 10‐cell metal BP fuel cell stack. The degradations of the average voltage and individual cell voltage in fuel cell stack were analyzed. To investigate the degradation mechanism, the stack was disassembled and the morphologies and compositions of no. 1, no. 5, and no. 10 cells after 2000 hours were characterized by SEM, TEM, and ASS. The results indicated that at 800 mA/cm², the voltage decay rate is 42.303 μV/hour and the voltage decay percentage of the stack is 14.34% after 2000 hours according to the linearly fitting result. According to the US Department of Energy (DOE) definition of fuel cell stack life, only the voltage decay rate of OCV and the tenth cell is lower than the maximum voltage degradation rates of 10 000 hours. The decreases of homogeneity of stack were the main reason for its performance degradation. Especially for the tenth cell, its performance has almost no drop. The main failure reason of this metal BP stack is structural design rather than metal corrosion. The losses of Pt catalyst and C supporting are the main reason of performance degradation.     

Preliminary experimental study of the performances for a print circuit board based planar PEMFC stack

This paper presents a novel planar proton exchange membrane fuel cell (PEMFC) stack designed for portable electronic devices, consisting of twenty homemade membrane electrode assemblies (MEAs) arranged on a planar surface and three printed circuit boards (PCBs, including anode, interlayer and cathode PCBs) used to load these MEAs. The current collectors and electrical connectors are manufactured using printed circuit technology. The inlet holes of reaction gases are also machined on PCB substrates. The output performance tests are performed on the MEAs and the assembled planar PEMFC stack. The results show that the power densities of the MEAs and the planar PEMFC stack are 0.6 W/cm² and 0.361 W/cm² at rated voltage under ambient temperature and forced convection air conditions, respectively. The stability tests are also conducted on the planar PEMFC stack, and the results show no significant fluctuations in output current. The feasibility of the application of planar PEMFC stacks in portable electronic devices is preliminarily demonstrated, and the improvement directions for further improving the output performance are proposed accordingly.     

Performance optimization of polymer electrolyte membrane fuel cells using the Nelder-Mead algorithm

The direct-search simplex method for function optimization has been adapted to performance optimization of polymer electrolyte membrane fuel cells (PEMFCs). The established method is strongly application oriented and uses only experimentally determined data for optimization. It is not restricted to discrete parameters optimums and does not require the use of third-party software or computational resources. Hence, it is easy to implement in fuel cell testing stations. The optimization consists of finding, for a given fuel cell load, an optimum set of values of the 7 fuel cell operating parameters: the fuel cell temperature, the reactants' stoichiometric ratios, the reactants' inlet relative humidity, and the reactants' outlet pressures, resulting in the highest fuel cell performance. The performance is measured using a scalar function of the operating parameters and the load and can be defined according to needs.Two PEMFC performance functions: the fuel cell voltage and the system-related fuel cell efficiency were optimized using the procedure for practically sized PEMFC stacks of two designs. With respect to the nominal operating conditions defined as optimal for each stack design by its manufacturer, the gains from the optimization procedure were up to over 12% and up to over 7% for the stack voltage and efficiency, respectively. The validation of the procedure involved 5 stack specimens and four laboratories and consistent results were obtained.     

Energy processing from fuel-cell systems using a high-gain power dc-dc converter: Analysis,design, and implementation

The electrolyte membrane fuel cell (PEMFC) is characterized by a low and unregulated output voltage; thus, an interface between source and load is required for processing the generated energy by the PEMFC. In this paper, a solution for processing the energy generated by a PEMFC is given. A switching regulator is developed by using a quadratic boost converter with a single switch (QBC-SS). The controller for the QBC-SS is designed using average current-mode (ACM) control, which is easy to implement using analog circuits. The proposed switching regulator ensures high conversion ratios, output voltage regulation, adequate dynamic performance, and stability. On the other hand, a model with static characteristics for the PEMFC electrical behavior is proposed, which can be used for modeling and control purposes. This model consists of three parameters, which are computed using experimental data of the PEMFC stack. A laboratory prototype of 400 W is used to verify the analytical results. As an input source, a PEMFC system is used. The output voltage of the PEMFC stack ranges from 41 V to 24 V, which depends on the generated current. Experimental results applying load step changes and frequency response analysis are shown.     

Experimental analysis of the performance of the air supply system in a 120 kW polymer electrolyte membrane fuel cell system

For analyzing the performance of 120 kW polymer electrolyte membrane fuel cell (PEMFC) system and its air supply system, an air system test bench was built, then applied on a 120 kW PEMFC system test bench composed of air supply subsystem, hydrogen supply subsystem, stack, cooling subsystem and electronic control subsystem. The strategy composed of feedforward table and Piecewise proportional integral (PI) feedback control strategy is employed to regulate the flow rate and pressure of air supply system. Firstly, the air compressor map and the mapping relationship between the speed of air compressor, opening of back-pressure valve and stack current are obtained by carrying out experiments on the PEMFC air system bench. Then, the max output performance, steady-state performance, the startup performance, the dynamic response abilities of PEMFC system are tested, respectively. During the experiments, performances under different test conditions were analyzed by comparing parameters such as voltage inconsistency, average voltage, minimum voltage, voltage range, net power of the PEMFC system, and stack power. The test results show that the air supply system can provide qualified flow rate and pressure for the PEMFC stack. The peak power of the stack is 120 kW and net power of the system is 97 kW when the current is 538 A. The response time from rated net power to idle net power is 12 s and from idle net power to rated net power is 23 s. The overshoot of average voltage and minimum voltage in the process of increasing load is both 0.01 V, which are 0.015 V and 0.02 V lower than that when the load is decreased, respectively. The dynamic response speed and stability of the PEMFC system in the process of decreasing the load are better than those in the process of increasing the load.     

Application of thermal imaging to validate a heat transfer model for polymer electrolyte fuel cells

Heat management in polymer electrolyte membrane fuel cells (PEMFCs) plays a vital role in stack performance and durability, and overall system efficiency. A computational model assembled by the authors has been used to study the heat generated and distributed in single-cell and two-cell PEMFC stacks, with a focus on temperature variation on the external surfaces of the stack under different heat loads.     

Parameters extraction of PEMFC's model using manta rays foraging optimizer

In this article, a recently developed bio-inspired based manta rays foraging optimizer (MRFO) is attempted for reliable and accurate extraction of the model uncertain parameters of proton exchange membrane fuel cells (PEMFCs). The parameter estimation is formulated as a non-linear optimization problem subject to set of restrictions. The great development and tremendous revolution of computation heuristic-based algorithms are the impetus of the authors to apply the MRFO to solve this constrained optimization problem resulting in a precise PEMFC model. Three case studies of typical field PEMFC stacks namely Ballard type Mark V, NedStack type PS6, and Horizon type H-12. Various I to V datasets are demonstrated to appraise the performance of MRFO among other recent optimizers available in the literature. To be objective and for sake of quantifications, the best scores of minimum fitness values are 0.8533, 2.1360, and 0.0966 for the later said PEMFC stacks, correspondingly. At a later stage, production of various characteristics under varying operating conditions such as changeable cell temperature and regulating pressures are established using the generated best values of PEMFCs model. Further calculations of statistical indices are performed to validate the robustness of obtained results by the MRFO. Through comprehensive performance assessments, it can be confirmed that MRFO is very promising tool for the effective extraction of PEMFCs' model and suggested to be applied for solving other engineering problems.     

A semiempirical dynamic model of reversible open circuit voltage drop in a PEM fuel cell

Fuel cell voltage modeling is important for fundamental research. The main focus of previous studies has been the working voltage segment, whereas the accuracy of the open circuit voltage (OCV), especially the dynamic OCV change process, has been ignored. A semiempirical model including the OCV and an electrochemical model has been proposed in this study to clarify the reversible voltage drop process. A mixed cathode potential drop that is assumed as corresponding to a piecewise function relationship with an active surface area is introduced in this study. Fitting results exactly coincide with the original data in 2 modes, namely a quasistatic condition in a bench test and a dynamic condition in a fuel cell city bus. In the dynamic OCV drop process, the voltage drop due to the hydrogen crossover current approximately corresponds to 0.003 V and the mixed cathode potential drop approximately corresponds to 0.02 V.     

A novel online degradation model for proton exchange membrane fuel cell based on online transfer learning

A novel online degradation prediction model is proposed to prognosticate the future degradation trend (FDT) of proton exchange membrane fuel cell (PEMFC) stack in this paper. In order to overcome the fact that existing FDT prediction methods of PEMFC stack based on data-driven model rely on the assumption that the operating conditions of the training data and testing data need to be consistent, an end-to-end prediction algorithm based on the combination of transfer learning and transformer neural network, referred to as TLTNN, is proposed to predict the FDT of PEMFC stack. Besides, in order to demonstrate the effectiveness and superiority of the proposed method in prognostics tasks of PEMFC stack FDT, the prediction performance is validated on the PEMFC test system. The results show that the RMSE, MAE and MAPE values of the predicted degradation voltage are 0.00598 V, 0.004842 V and 0.1518%, respectively, which indicates that the proposed TLTNN strategy based on transfer online learning can be used to predict the degradation voltage of PEMFC stack and the superiority of the proposed method is better, thus solving the problem that the distribution of training and test data must be the same in traditional machine learning models.     

Operating characteristics of an air-cooling PEMFC for portable applications

Optimal design and proper operation is important to get designed output power of a polymer electrolyte membrane fuel cell (PEMFC) stack. The air-cooling fuel cell stack is widely used in sub kW PEMFC systems. The purpose of this study is to analyze the operating conditions affecting the performance of an air-cooling PEMFC which is designed for portable applications. It is difficult to maintain well balanced operating conditions. These parameters are the relative humidity, the temperature of the stack, the utility ratio of the reactant gas and so on. In this study a 500 W rate air-cooling PEMFC was fabricated and tested to evaluate the design performance and to determine optimal operating conditions. Moreover, basic modeling also is carried out. These results can be used as design criteria and optimal operating conditions for portable PEMFCs.     

Voltage reversal during microbial fuel cell stack operation

Microbial fuel cells (MFC) can be used to directly generate electricity from organic matter, but the voltage produced by a single reactor is only ∼0.5 V. Voltage can be increased by stacking cells, i.e. by linking individual reactors in series, as is commonly done with hydrogen fuel cells, to provide a higher voltage output. A two-cell air-cathode MFC stack tested here produced a working voltage of 0.9 V (external load 500 Ω) and had an open circuit voltage (OCV) of 1.3 V when operated in fed batch mode under substrate-sufficient conditions. When multiple cells are stacked together, however, charge reversal can result in the reverse polarity of one or more cells and a loss of power generation. We investigated the causes of charge reversal and the impact of prolonged reversal on power generation using a two air-cathode MFCs stack. When voltage began to decline at the end of a fed batch cycle, we observed voltage reversal with one cell producing a working voltage of 0.6 V, and the other cell having a reversed voltage of −0.58 V, producing only a minimal stack voltage of 0.02 V. The reason for the voltage reversal was shown to be fuel starvation, resulting in a loss of bacterial activity. Voltage reversal adversely affected bacteria on the anode of the affected cell, as shown by a relative decrease in cell performance following a cycle of starvation (no feeding). The control of voltage reversal will be crucial for long-term operation of MFCs in series. Rapid feeding of a cell can restore positive voltage generation, but the long-term impact of charge reversal will be inactivation of bacteria and it will require that the affected cells be short-circuited to maintain stack power production. A better understanding of the long term effects of voltage reversal on power generation by MFC stacks is needed in order to efficiently increase voltage production by using stacked MFC systems.     

Artificial ecosystem optimizer for parameters identification of proton exchange membrane fuel cells model

Modeling and optimization of the proton exchange membrane fuel cells (PEMFCs) raise a crucial challenge due to their characteristics of multi-variability and nonlinearity natures. To ensure an accurate and reliable model for PEMFCs, best values of their uncertain parameters should be defined carefully. A conventional artificial ecosystem optimizer (AEO) and an improved and developed AEO (called IAEO) are used to realize the later aim. In the proposed IAEO, a dynamic crossover pattern is presented to enable the algorithm to achieve better solution, and also prevent the stuck in local optima. Sum of squared errors (SSE) defines the fitness function subjected to set of practical constraints. The proposed IAEO-based algorithm is analyzed and demonstrated on different typical benchmarking PEMFCs modules widely used in the literature. Comprehensive simulations and performance assessments are carried out on the PEMFCs models to affirm the efficacy and robustness of the proposed IAEO based on methodology while simulating the commercial PEMFC stacks behavior in regards to the experimental data. In this context, best values of SSE resulted by IAEO are 0.0116, 0.3359, and 2.1459, for BCS 500-W, 250 W stack, and NedStack PS6, respectively that are very competitive values among other challenging methodologies. This noticeably indicates that the developed IAEO-based method gives better efficiency with the highest robustness and convergence speed compared with the other methods. At a later stage, dynamic performance of PEMFCs stacks are carried out. It can be established that the reported outcomes affirm the superiority and reliability of the IAEO algorithm over the conventional AEO and the other competitors.     

Cold start optimization of the proton-exchange membrane fuel cell by penetrating holes in the cathode micro-diffusion layer

Enhancing the cold start ability of proton-exchange membrane fuel cells (PEMFCs) can widely apply fuel cells in a cold environment. In this study, PEMFC cold start performance was significantly affected by penetrating holes in a cathode micro-diffusion layer (MDL). The testing MDLs were mechanically processed with 0.2-mm-diameter and 0.5-mm-diameter penetrating holes, respectively, and the normal MDL as reference. Fundamental water permeance and PEMFC performance tests at normal temperature were conducted beforehand for all MDLs. The cold start of the fuel cell was experimentally studied by monitoring PEMFC voltage and high-frequency impedance. Results show that the 0.5-mm-diameter penetrating holes improve the water permeance at least three orders of magnitude than the normal MDL. The fuel cell using the MDL with the 0.2-mm-diameter penetrating holes performs best in regular operation at 70 °C and in cold starts from ?7 °C.     

Tuning of PEM fuel cell model parameters for prediction of steady state and dynamic performance under various operating conditions

Many models are available with various degrees of complexity to study the behaviour of Proton Exchange Membrane Fuel Cells (PEMFC) under varying operating conditions. To our knowledge no model has been developed from single cells to multiple cells with increased electrode area for PEMFC stacks along with power conditioners, by considering the dynamic characteristics of the fuel cells under the influence of stoichiometry, humidity ratio and their response during their integration with power conditioners. We have developed a model using Matlab to study the transient response of the cell for 30 cm², which has been extended to a multicell stack of 1.2 kW capacity of electrode area 150 cm². The developed model has been validated using PEMFC single cells and stacks, by considering partial pressure of hydrogen, oxygen, and water as three states, anode fuel utilization and all three losses. This model is proposed to evaluate the transient response of all the stacks developed at Centre for Fuel Cell Technology (CFCT) ranging from a few watts to 10 kW that are integrated with various power conditioners depending on the applications.     

Enhanced reliability of planar-type solid oxide fuel cell stack incorporating leakage gas induction channels

Planar type solid oxide fuel cell stacks have been studied for use as commercial products because of their high energy density and environment-friendly operation. They employ a gasket as a sealant as it enables easy assembly and repair. However, its imperfect sealing property, detrimental to long-term operation, has limited its introduction. Here, a stack design with a gasket sealant including a leakage gas induction channel is developed. The leakage gas induction channel within the gasket sealant prevents gas leakage of fuel and air to the opposite electrode and ensures the stack's stable operation. The stack design's reliability is confirmed via a heating-cycle test and an open circuit voltage to a 0.7 V voltage control test. In-situ gas chromatography analysis shows that the diffusion of gases effectively reduces by releasing them outside the stack through the leakage gas induction channel.