Continuous Lithium-Ion Extraction From Seawater and Mine Water With a Fuel Cell System and Ceramic Membranes

The demand for electronic devices that utilize lithium is steadily increasing in this rapidly advancing technological world.Obtaining high-purity lithium in an environmentally friendly way is challenging by using commercialized methods.Herein,we propose the first fuel cell system for continuous lithium-ion extraction using a lithium superionic conductor membrane and advanced electrode.The fuel cell system for extracting lithium-ion has demonstrated a twofold increase in the selectivity of Li^(+)/Na^(+)while producing electricity.Our data show that the fuel cell with a titania-coated electrode achieves 95%lithium-ion purity while generating 10.23 Wh of energy per gram of lithium.Our investigation revealed that using atomic layer deposition improved the electrode's uniformity,stability,and electrocatalytic activity.After 2000 cycles determined by cyclic voltammetry,the electrode preserved its stability.

Adaptive inverse control of air supply flow for proton exchange membrane fuel cell systems

To prevent the oxygen starvation and improve the system output performance, an adaptive inverse control （AIC） strategy is developed to regulate the air supply flow of a proton exchange membrane fuel cell （PEMFC） system in this paper. The PEMFC stack and the air supply system including a compressor and a supply manifold are modeled for the purpose of performance analysis and controller design. A recurrent fuzzy neural network （RFNN） is utilized to identify the inverse model of the controlled system and generates a suitable control input during the abrupt step change of external disturbances. Compared with the PI controller, numerical simulations are performed to validate the effectiveness and advantages of the proposed AIC strategy.

Data-driven nonlinear control of a solid oxide fuel cell system

Solid oxide fuel cells (SOFCs) are considered to be one of the most important clean,distributed resources. However,SOFCs present a challenging control problem owing to their slow dynamics,nonlinearity and tight operating constraints. A novel data-driven nonlinear control strategy was proposed to solve the SOFC control problem by combining a virtual reference feedback tuning (VRFT) method and support vector machine. In order to fulfill the requirement for fuel utilization and control constraints,a dynamic constraints unit and an anti-windup scheme were adopted. In addition,a feedforward loop was designed to deal with the current disturbance. Detailed simulations demonstrate that the fast response of fuel flow for the current demand disturbance and zero steady error of the output voltage are both achieved. Meanwhile,fuel utilization is kept almost within the safe region.

Efficiency and Size Optimization of a General Solid Oxide Fuel Cell System

An irreversible model of high temperature solid oxide fuel cells( SOFCs) working at steady-state is developed,devoted to performing the optimization with regard to two objectives:minimization of the fuel cell size and maximization of the system efficiency. The performance characteristics of the system are analyzed in details, illustrated by the curves of power density,efficiency and voltage. Genetic algorithm is used to perform the multi-objective optimization with four decision variables: the operating pressure, the fuel stoichiometric ratio, the air stoichiometric ratio and the current density. A Pareto set giving a quantative description of the trade-off between the two objectives is used to analyze the results. Optimization results prove the existence of optimal designs region for a 50 kW system with efficiency from 43% corresponding to a 14. 6 m2 electrolyte area to 48% corresponding to a 25.4 m2 electrolyte area. The SOFC model used is general and the optimization results could be applied to the practical SOFC design.

Nonlinear State Feedback Control of PEM Fuel Cell Systems

In this paper, the nonlinear state feedback controller has been developed to control the pressures of the oxygen and the hydrogen in the PEM（Proton Exchange Membrane） fuel cell system. Nonlinear model of the PEM fuel cell system was introduced to study the design problems of the state observer and model based controller. A cascade observer using the filtering technique was used to estimate the pressure derivatives of the cathode and the anode in the system. In order to estimate the pressures of the cathode and the anode, the sliding mode observer was designed by using these pressure derivatives. To estimate the oxygen pressure and the hydrogen pressure in the system, the nonlinear state observer was designed by using the cathode pressure estimates and the anode it. These results will be very useful to design the state feedback controller. The validity of the proposed observers and the controller has been investigated by using a Lyapunov＇s stability analysis strategy.

Performance test of a 5 kW solid oxide fuel cell system under high fuel utilization with industrial fuel gas feeding

As the demand for green energy with high efficiency and low carbon dioxide(CO2)emissions has increased,solid oxide fuel cells(SOFCs)have been intensively developed in recent years.Integrated gasification fuel cells(IGFCs)in particular show potential for large-scale power generation to further increase system efficiency.Thus,for commercial application of IGFCs,it is important to design reliable multi-stacks for large systems that show long-term stability and practical fuel gas for application to industrial equipment.In this work,a test rig(of a 5 kW SOFC system,with syngas from industrial gasifiers as fuel)was fabricated and subjected to long-term tests under high fuel utilization to investigate its performance.The maximum steady output power of the system was 5700 W using hydrogen and 5660 W using syngas and the maximum steady electrical efficiency was 61.24%while the fuel utilization efficiency was 89.25%.The test lasted for more than 500 h as the fuel utilization efficiency was larger than 83%.The performances of each stack tower were almost identical at both the initial stage and after long-term operation.After 500 h operation,the performances of the stack towers decreased only slightly under lower current and showed almost no change under high current.These results demonstrate the reliability of the multi-stack design and the prospect of this SOFC power-generation system for further enlarging its application in a MWth demonstration.

Dynamic Control of Electric Output Characteristics of Proton Exchange Membrane Fuel Cell System

This paper discusses dynamic characteristics of proton exchange membrane fuel cell (PEMFC) under rapid fluctuation of power demand. Wavelet neural network is adopted in the identification of the characteristic curve to predict the voltage. The system control scheme of the voltage and power is introduced. The corresponding schemes for voltage and power control are studied. MATLAB is used to simulate the control system. The results reveal that the adopted control schemes can produce expected effects. Corresponding anti-disturbance and robustness simulation are also carried out. The simulation results show that the implemented control schemes have better robustness and adaptability.

Optimal Allocation of a Hybrid Wind Energy-Fuel Cell System Using Different Optimization Techniques in the Egyptian Distribution Network

This paper presents an optimal proposed allocating procedure for hybrid wind energy combined with proton exchange membrane fuel cell (WE/PEMFC) system to improve the operation performance of the electrical distribution system (EDS). Egypt has an excellent wind regime with wind speeds of about 10 m/s at many areas. The disadvantage of wind energy is its seasonal variations. So, if wind power is to supply a significant portion of the demand, either backup power or electrical energy storage (EES) system is needed to ensure that loads will be supplied in reliable way. So, the hybrid WE/PEMFC system is designed to completely supply a part of the Egyptian distribution system, in attempt to isolate it from the grid. However, the optimal allocation of the hybrid units is obtained, in order to enhance their benefits in the distribution networks. The critical buses that are necessary to install the hybrid WE/ PEMFC system, are chosen using sensitivity analysis. Then, the binary Crow search algorithm (BCSA), discrete Jaya algorithm (DJA) and binary particle swarm optimization (BPSO) techniques are proposed to determine the optimal operation of power systems using single and multi-objective functions (SOF/MOF). Then, the results of the three optimization techniques are compared with each other. Three sensitivity factors are employed in this paper, which are voltage sensitivity factor (VSF), active losses sensitivity factor (ALSF) and reactive losses sensitivity factor (RLSF). The effects of the sensitivity factors (SFs) on the SOF/MOF are studied. The improvement of voltage profile and minimizing active and reactive power losses of the EDS are considered as objective functions. Backward/forward sweep (BFS) method is used for the load flow calculations. The system load demand is predicted up to year 2022 for Mersi-Matrouh City as a part of Egyptian distribution network, and the design of the hybrid WE/PEMFC system is applied. The PEMFC system is designed considering simplified mathematical expressions. The economics of operation of both WE and PEMFC system are also presented. The results prove the capability of the proposed procedure to find the optimal allocation for the hybrid WE/PEMFC system to improve the system voltage profile and to minimize both active and reactive power losses for the EDS of Mersi-Matrough City.

PEM Fuel Cell System Evaluation Using Operational Data and Updated Matlab/Simulink Simulation Tools

The aim of this paper is the evaluation of the performance of a low pressure PEM （proton exchange membrane） fuel cell stack to step load changes, which are characteristic of standalone fuel cell system applications. The goal is a better understanding of the electrical behavior of the FC （fuel cell）, as a result of the electrochemical processes, via the cell＇s voltage characteristic during transient response. While changing the load, the performance of significant parameters affected such as temperature, pressure, purge status etc. are registered and evaluated. The analysis and experiment are based on a low pressure 1.2 kW PEM fuel cell stack （NEXAS power module）. Then, the experiment is simulated using Matlab/Simulink tools, while PCU （power conditioning units） are added in order to control power flow for enhanced performance. Finally, both operational and simulation data are compared to each other showing that simple PCUs applications can improve system＇s efficiency.

Adaptive neural network observer for proton-exchange membrane fuel cell system

This paper develops an adaptive neural network(NN)observer for proton-exchange membrane fuel cells(PEMFCs).Indeed,information on the oxygen excess ratio(OER)value is crucial to ensure optimal management of the durability and reliability of the PEMFC.The OER indicator is computed from the mass of oxygen and nitrogen inside the PEMFC cathode.Unfortunately,the measurement process of both these masses is difficult and costly.To solve this problem,the design of a PEMFC state observer is attractive.However,the behaviour of the fuel cell system is highly non-linear and its modelling is complex.Due to this constraint,a multilayer perceptron neural network(MLPNN)-based observer is proposed in this paper to estimate the oxygen and nitrogen masses.One notable advantage of the suggested MLPNN observer is that it does not require a database to train the NN.Indeed,the weights of the NN are updated in real time using the output error.In addition,the observer parameters,namely the learning rate and the damping factor,are online adapted using the optimization tools of extremum seeking.Moreover,the proposed observer stability analysis is performed using the Lyapunov theory.The observer performances are validated by simulation under MATLAB®/Simulink®.The supremacy of the proposed adaptive MLPNN observer is highlighted by comparison with a fixed-parameter MLPNN observer and a classical high-gain observer(HGO).The mean rela-tive error value of the excess oxygen rate is considered the performance index,which is equal to 1.01%for an adaptive MLPNN and 3.95%and 9.95%for a fixed MLPNN and HGO,respectively.Finally,a robustness test of the proposed observer with respect to measurement noise is performed.

Model reduction of fractional impedance spectra for time–frequency analysis of batteries, fuel cells, and supercapacitors

Joint time–frequency analysis is an emerging method for interpreting the underlying physics in fuel cells,batteries,and supercapacitors.To increase the reliability of time–frequency analysis,a theoretical correlation between frequency-domain stationary analysis and time-domain transient analysis is urgently required.The present work formularizes a thorough model reduction of fractional impedance spectra for electrochemical energy devices involving not only the model reduction from fractional-order models to integer-order models and from high-to low-order RC circuits but also insight into the evolution of the characteristic time constants during the whole reduction process.The following work has been carried out:(i)the model-reduction theory is addressed for typical Warburg elements and RC circuits based on the continued fraction expansion theory and the response error minimization technique,respectively;(ii)the order effect on the model reduction of typical Warburg elements is quantitatively evaluated by time–frequency analysis;(iii)the results of time–frequency analysis are confirmed to be useful to determine the reduction order in terms of the kinetic information needed to be captured;and(iv)the results of time–frequency analysis are validated for the model reduction of fractional impedance spectra for lithium-ion batteries,supercapacitors,and solid oxide fuel cells.In turn,the numerical validation has demonstrated the powerful function of the joint time–frequency analysis.The thorough model reduction of fractional impedance spectra addressed in the present work not only clarifies the relationship between time-domain transient analysis and frequency-domain stationary analysis but also enhances the reliability of the joint time–frequency analysis for electrochemical energy devices.

Recent progresses in the development of tubular segmented-in-series solid oxide fuel cells:Experimental and numerical study

Solid oxide fuel cells(SOFCs)have attracted a great deal of interest because they have the highest efficiency without using any noble metal as catalysts among all the fuel cell technologies.However,traditional SOFCs suffer from having a higher volume,current leakage,complex connections,and difficulty in gas sealing.To solve these problems,Rolls-Royce has fabricated a simple design by stacking cells in series on an insulating porous support,resulting in the tubular segmented-in-series solid oxide fuel cells(SIS-SOFCs),which achieved higher output voltage.This work systematically reviews recent advances in the structures,preparation methods,perform-ances,and stability of tubular SIS-SOFCs in experimental and numerical studies.Finally,the challenges and future development of tubular SIS-SOFCs are also discussed.The findings of this work can help guide the direction and inspire innovation of future development in this field.

Boosting oxygen reduction activity and CO_(2) resistance on bismuth ferrite-based perovskite cathode for low-temperature solid oxide fuel cells below 600℃

Developing efficient and stable cathodes for low-temperature solid oxide fuel cells(LT-SOFCs) is of great importance for the practical commercialization.Herein,we propose a series of Sm-modified Bi_(0.7-x)Sm_xSr_(0.3)FeO_(3-δ) perovskites as highly-active catalysts for LT-SOFCs.Sm doping can significantly enhance the electrocata lytic activity and chemical stability of cathode.At 600℃,Bi_(0.675)Sm_(0.025)Sr_(0.3)FeO_(3-δ)(BSSF25) cathode has been found to be the optimum composition with a polarization resistance of 0.098 Ω cm^2,which is only around 22.8% of Bi_(0.7)Sr_(0.3)FeO_(3-δ)(BSF).A full cell utilizing BSSF25 displays an exceptional output density of 790 mW cm^(-2),which can operate continuously over100 h without obvious degradation.The remarkable electrochemical performance observed can be attributed to the improved O_(2) transport kinetics,superior surface oxygen adsorption capacity,as well as O_(2)p band centers in close proximity to the Fermi level.Moreover,larger average bonding energy(ABE) and the presence of highly acidic Bi,Sm,and Fe ions restrict the adsorption of CO_(2) on the cathode surface,resulting in excellent CO_(2) resistivity.This work provides valuable guidance for systematic design of efficient and durable catalysts for LT-SOFCs.

Critical role of carbon support in metal nanoaggregate facilitating Fe-N-C catalyst for PEM fuel cell application

Metal nanoaggregates can simultaneously enhance the activity and stability of Fe-N-C catalysts in proton-exchange-membrane fuel cells(PEMFC).Previous studies on the relevant mechanism have focused on the direct interaction between FeN_(4)active sites and metal nanoaggregates.However,the role of carbon support that hosts metal nanoaggregates and active sites has been overlooked.Here,a Fe-N-C catalyst encapsulating inactive gold nanoparticles is prepared as a model catalyst to investigate the electronic tuning of Au nanoparticles(NPs)towards the carbon support.Au NPs donate electrons to carbon support,making it rich inπelectrons,which reduces the work function and regulates the electronic configuration of the FeN_(4)sites for an enhanced ORR activity.Meanwhile,the electron-rich carbon support can mitigate the electron depletion of FeN_(4)sites caused by carbon support oxidation,thereby preserving its high activity.The yield and accumulation of H_(2)O_(2)are thus alleviated,which delays the oxidation of the catalyst and benefits the stability.Due to the electron-rich carbon support,the composite catalyst achieves a top-level peak power density of 0.74 W/cm^(2) in a 1.5 bar H_(2)-air PEMFC,as well as the improved stability.This work elucidates the key role of carbon support in the performance enhancement of the FeN-C/metal nanoaggregate composite catalysts for fuel cell application.

Al^(3+) doped CeO_(2) for proton conducting fuel cells

Developing high ionic conducting electrolytes is crucial for applying proton-conducting fuel cell(PCFCs)practically.The cur-rent study investigates the effect of alumina on the structural,morphological,electrical,and electrochemical properties of CeO_(2).Lattice oxygen vacancies are induced in CeO_(2) by a general doping concept that enables fast ionic conduction at low-temperature ranges(300-500℃)for PCFCs.Rietveld refinement of the X-ray diffraction(XRD)patterns established the pure cubic fluorite structure of Al-doped CeO_(2)(ADC)samples and confirmed Al ions’fruitful integration in the CeO_(2) lattice.The electronic structure of the alumina-doped ceria of the materials(10ADC,20ADC,and 30ADC)has been investigated.As a result,it was found that the best composition of 30ADC-based electrolytes induced maximum lattice oxygen vacancies.The corresponding PCFC exhibited a maximum power output of 923 mW/cm^(2)at 500℃.Moreover,the investigation proves the proton-conducting ability of alumina-doped ceria-based fuel cells by using an oxide ion-blocking layer.

Enhancing layered perovskite ferrites with ultra-high-density nanoparticles via cobalt doping for ceramic fuel cell anode

Nanoparticles anchored on the perovskite surface have gained considerable attention for their wide-ranging applications in heterogeneous catalysis and energy conversion due to their robust and integrated structural configuration.Herein,we employ controlled Co doping to effectively enhance the nanoparticle exsolution process in layered perovskite ferrites materials.CoFe alloy nanoparticles with ultra-high-density are exsolved on the(PrBa)_(0.95)(Fe_(0.8)Co_(0.1)Nb_(0.1))2O_(5+δ)(PBFCN_(0.1))surface under reducing atmosphere,providing significant amounts of reaction sites and good durability for hydrocarbon catalysis.Under a reducing atmosphere,cobalt facilitates the reduction of iron cations within PBFCN_(0.1),leading to the formation of CoFe alloy nanoparticles.This formation is accompanied by a cation exchange process,wherein,with the increase in temperature,partial cobalt ions are substituted by iron.Meanwhile,Co doping significantly enhance the electrical conductivity due to the stronger covalency of the Cosingle bondO bond compared with Fesingle bondO bond.A single cell with the configuration of PBFCN_(0.1)-Sm_(0.2)Ce_(0.8)O_(1.9)(SDC)|SDC|Ba_(0.5)Sr_(0.5)Co_(0.8)Fe_(0.2)O_(3−δ)(BSCF)-SDC achieves an extremely low polarization resistance of 0.0163Ωcm^(2)and a high peak power density of 740 mW cm^(−2)at 800℃.The cell also shows stable operation for 120 h in H_(2)with a constant current density of 285 mA cm^(−2).Furthermore,employing wet C_(2)H_(6)as fuel,the cell demonstrates remarkable performance,achieving peak power densities of 455 mW cm^(−2)at 800℃and 320 mW cm^(−2)at 750℃,marking improvements of 36%and 70%over the cell with(PrBa)_(0.95)(Fe_(0.9)Nb_(0.1))_(2)O_(5+δ)(PBFN)-SDC at these respective temperatures.This discovery emphasizes how temperature influences alloy nanoparticles exsolution within doped layered perovskite ferrites materials,paving the way for the development of high-performance ceramic fuel cell anodes.

Probing the Efficiency of PPMG-Based Composite Electrolytes for Applications of Proton Exchange Membrane Fuel Cell

PPMG-based composite electrolytes were fabricated via the solution method using the polyvinyl alcohol and polyvinylpyrrolidone blend reinforced with various contents of sulfonated inorganic filler.Sulfuric acid was employed as the sulfonating agent to functionalize the external surface of the inorganic filler,i.e.,graphene oxide.The proton conductivities of the newly prepared proton exchange membranes(PEMs)were increased by increasing the temperature and content of sulfonated graphene oxide(SGO),i.e.,ranging from 0.025 S/cm to 0.060 S/cm.The induction of the optimum level of SGO is determined to be an excellent route to enhance ionic conductivity.The single-cell performance test was conducted by sandwiching the newly prepared PEMs between an anode(0.2 mg/cm^(2) Pt/Ru)and a cathode(0.2 mg/cm^(2) Pt)to prepare membrane electrode assemblies,followed by hot pressing under a pressure of approximately 100 kg/cm^(2) at 60℃for 5–10 min.The highest power densities achieved with PPMG PEMs were 14.9 and 35.60 mW/cm^(2) at 25℃and 70℃,respectively,at ambient pressure with 100%relative humidity.Results showed that the newly prepared PEMs exhibit good electrochemical performance.The results indicated that the prepared composite membrane with 6 wt%filler can be used as an alternative membrane for applications of high-performance proton exchange membrane fuel cell.

Performance Degradation Prediction of Proton Exchange Membrane Fuel Cell Based on CEEMDAN-KPCA and DA-GRU Networks

In order to improve the performance degradation prediction accuracy of proton exchange membrane fuel cell(PEMFC),a fusion prediction method(CKDG)based on adaptive noise complete ensemble empirical mode decomposition(CEEMDAN),kernel principal component analysis(KPCA)and dual attention mechanism gated recurrent unit neural network(DA-GRU)was proposed.CEEMDAN and KPCA were used to extract the input feature data sequence,reduce the influence of random factors,and capture essential feature components to reduce the model complexity.The DA-GRU network helps to learn the feature mapping relationship of data in long time series and predict the changing trend of performance degradation data more accurately.The actual aging experimental data verify the performance of the CKDG method.The results show that under the steady-state condition of 20%training data prediction,the CKDA method can reduce the root mean square error(RMSE)by 52.7%and 34.6%,respectively,compared with the traditional LSTM and GRU neural networks.Compared with the simple DA-GRU network,RMSE is reduced by 15%,and the degree of over-fitting is reduced,which has higher accuracy.It also shows excellent prediction performance under the dynamic condition data set and has good universality.

Effect of carbon material and surfactant on ink property and resulting surface cracks of fuel-cell microporous layers

Ensuring the consistency of electrode structure in proton-exchange-membrane fuel cells is highly desired yet challenging because of wide-existing and unguided cracks in the microporous layer(MPL). The first thing is to evaluate the homogeneity of MPL with cracks quantitatively. This paper proposes the homogeneity index of a full-scale MPL with an area of 50 cm~2, which is yet to be reported in the literature to our knowledge. Besides, the effects of the carbon material and surfactant on the ink and resulting MPL structure have been studied. The ink with a high network development degree produces an MPL with low crack density, but the ink with high PDI produces an MPL with low crack homogeneity. The polarity of the surfactant and the non-polarity of polytetrafluoroethylene(PTFE) are not mutually soluble,resulting in the heterogeneous PTFE distribution. The findings of this study provide guidelines for MPL fabrication.

Analysis of the Influence of Geometrical Parameters on the Performance of a Proton Exchange Membrane Fuel Cell

A suitable channel structure can lead to efficient gas distribution and significantly improve the power density of fuel cells.In this study,the influence of two channel design parameters is investigated,namely,the ratio of the channel width to the bipolar plate ridge width(i.e.,the channel ridge ratio)and the channel depth.The impact of these parameters is evaluated with respect to the flow pattern,the gas composition distribution,the temperature field and the fuel cell output capability.The results show that a decrease in the channel ridge ratio and an increase in the channel depth can effectively make the distributions of velocity,temperature and concentration more uniform in each channel and improve the output capability of the fuel cell.An increase in the channel ridge ratio and depth obviously reduces the flow resistance and improves the flow characteristics.