CFD Analysis of Spiral Flow Fields in Proton Exchange Membrane Fuel Cells

Proton exchange membrane fuel cells(PEMFCs)are largely used in various applications because of their pollution-free products and high energy conversion efficiency.In order to improve the related design,in the present work a new spiral flow field with a bypass is proposed.The reaction gas enters the flow field in the central path and diffuses in two directions through the flow channel and the bypass.The bypasses are arranged incrementally.The number of bypasses and the cross-section size of the bypasses are varied parametrically while a single-cell model of the PEMFC is used.The influence of the concentration of liquid water and oxygen in the cell on the performance of different flow fields is determined by means of Computational fluid dynamics(COMSOL Multiphysics software).Results show that when the bypass number is 48 and its cross-sectional area is 0.5 mm^(2),the cell exhibits the best performances.

Particle Swarm Optimization based predictive control of Proton Exchange Membrane Fuel Cell (PEMFC)

Proton Exchange Membrane Fuel Cells (PEMFCs) are the main focus of their current development as power sources because they are capable of higher power density and faster start-up than other fuel cells. The humidification system and output performance of PEMFC stack are briefly analyzed. Predictive control of PEMFC based on Support Vector Regression Machine (SVRM) is presented and the SVRM is constructed. The processing plant is modelled on SVRM and the predictive control law is obtained by using Particle Swarm Optimization (PSO). The simulation and the results showed that the SVRM and the PSO re-ceding optimization applied to the PEMFC predictive control yielded good performance.

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.

Recent Advances in Electrode Design Based on One-Dimensional Nanostructure Arrays for Proton Exchange Membrane Fuel Cell Applications

One-dimensional(1D)Pt-based electrocatalysts demonstrate outstanding catalytic activities and stability toward the oxygen reduction reaction(ORR).Advances in three-dimensional(3D)ordered electrodes based on 1D Pt-based nanostructure arrays have revealed great potential for developing highperformance proton exchange membrane fuel cells(PEMFCs),in particular for addressing the mass transfer and durability challenges of Pt/C nanoparticle electrodes.This paper reviews recent progress in the field,with a focus on the 3D ordered electrodes based on self-standing Pt nanowire arrays.Nanostructured thin-film(NSTF)catalysts are discussed along with electrodes made from Pt-based nanoparticles deposited on arrays of polymer nanowires,and carbon and TiO2 nanotubes.Achievements on electrodes from Pt-based nanotube arrays are also reviewed.The importance of size,surface properties,and the distribution control of 1D catalyst nanostructures is indicated.Finally,challenges and future development opportunities are addressed regarding increasing electrochemical surface area(ECSA)and quantifying oxygen mass transport resistance for 1D nanostructure array electrodes.

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.

Recent insights on iron based nanostructured electrocatalyst and current status of proton exchange membrane fuel cell for sustainable transport

Bridging the performance gap of the electrocatalyst between the rotating disk electrode(RDE) and membrane electrode assembly(MEA) level testing is the key to reducing the total cost of proton exchange membrane fuel cell(PEMFC) vehicles. Presently, platinum metal accounts for ~42% of the total cost of the PEMFC vehicles for usage in the cathode catalyst layer, where the sluggish oxygen reduction reaction(ORR) occurs. An alternative to the platinum catalyst, the Fe-N-C catalyst has attracted considerable interest for PEMFC due to its cost-effectiveness and high catalytic activity towards ORR. However, the excellent ORR activity of Fe-N-C obtained from RDE studies rarely translates the same performance into MEA operating conditions. Such a performance gap is mainly attributed to the lack of atomic-level understanding of Fe-N-C active sites and their ORR mechanism. Besides, unless the cost of expensive electrocatalyst is reduced, the total operation cost of the PEMFC vehicles remains constant. Therefore,developing highly efficient Fe-N-C catalysts from academic and industrial perspectives is critical for commercializing PEMFC vehicles. Here, the scope of the review is three-fold. First, we discussed the atomiclevel insights of Fe-N-C active sites and ORR mechanism, followed by unraveling the different iron-based nanostructured ORR electrocatalysts, including oxide, carbide, nitride, phosphide, sulfide, and singleatom catalysts. And then we bridged their ORR catalytic performance gap between the RDE and MEA tests for real operating conditions of PEMFC vehicles. Second, we focused on bridging the cost barriers of PEMFC vehicles between capital, operation, and end-user. Finally, we provided the path to achieve sustainable development goals by commercializing PEMFC vehicles for a better world.

Ultrasonic Spray Coating for Proton Exchange Membrane Fuel Cell

Ultrasound is now a widely used method for catalyst synthesis, catalyst support treatment, catalyst layer fabrication, membrane electrode assembly (MEA) fabrication, and humidifier etc. for fuel cell applications. Among the abovementioned uses, ultrasonic technology has been utilised mainly for MEA fabrication—especially since it has demonstrated the capability to produce ultralow platinum loadings. This paper reports the power density and cathode mass power density at peak power and 500 mA/cm2 conditions for ultrasonically spray coated MEAs. These MEAs were also produced with various Nafion content ratios and platinum loadings. The results indicate varying optimum values for different conditions.

New hybrid model of proton exchange membrane fuel cell

Model and simulation are good tools for design optimization of fuel cell systems. This paper proposes a new hybrid model of proton exchange membrane fuel cell (PEMFC). The hybrid model includes physical component and black-box com-ponent. The physical component represents the well-known part of PEMFC, while artificial neural network (ANN) component estimates the poorly known part of PEMFC. The ANN model can compensate the performance of the physical model. This hybrid model is implemented on Matlab/Simulink software. The hybrid model shows better accuracy than that of the physical model and ANN model. Simulation results suggest that the hybrid model can be used as a suitable and accurate model for PEMFC.

基于P-L双重特征提取的PEMFC系统故障诊断方法

针对质子交换膜燃料电池系统故障诊断问题,提出基于P-L双重特征提取的故障诊断方法。使用P-L双重特征提取对预处理后的样本数据进行特征提取,通过冗余变量剔除与二次特征提取,最大程度保留分类特征并有效降低样本数据维度。利用二叉树多类支持向量机与极限学习机对二维故障特征向量进行分类实现故障诊断。通过实例验证,对比线性判别分析的特征提取效果,P-L双重特征提取可使相同分类器测试集诊断准确率提高21.19%,诊断准确率达99.27%,实现了PEMFC系统膜干、氢气供应故障的精准快速诊断。

Modeling of Packed Bed Methanol Steam Reformer Integrated with Tubular High Temperature Proton Exchange Membrane Fuel Cell

This work proposes a novel tubular structure of high-temperature proton exchange membrane fuel cell(PEMFC)integrated with a built-in packed-bed methanol steam reformer to provide hydrogen for power output.A two-dimensional axisymmetric non-isothermal model was developed in COMSOL Multiphysics 5.4 to simulate the performance of a tubular high temperature proton membrane fuel cell and a packed bed methanol reformer.The model considers the coupling multi-physical processes,including methanol reforming reaction,water gas shift reaction,methanol cracking reaction as well as the heat,mass and momentum transport processes.The sub-model of the tubular packed-bed methanol reformer is validated between 433 K and 493 K with the experimental data reported in the literature.The sub-model of the high temperature proton exchange fuel cell is validated between 393 K and 433 K with the published literature.Our results show that power output and temperature distribution of the integrated unit depend on methanol flow rates and working voltages.It was suggested that stable power generation performance of 0.14 W/cm_(2)and temperature drop in methanol steam reformer of≤10 K could be achieved by controlling the methanol space-time ratio of≥250 kg·s/mol with working voltage at 0.6 V,even in the absence of an external heat source.

Exploration of the oxygen transport behavior in non-precious metal catalyst-based cathode catalyst layer for proton exchange membrane fuel cells

High cost has undoubtedly become the biggest obstacle to the commercialization of proton exchange membrane fuel cells(PEMFCs),in which Pt-based catalysts employed in the cathodic catalyst layer(CCL)account for the major portion of the cost.Although nonprecious metal catalysts(NPMCs)show appreciable activity and stability in the oxygen reduction reaction(ORR),the performance of fuel cells based on NPMCs remains unsatisfactory compared to those using Pt-based CCL.Therefore,most studies on NPMC-based fuel cells focus on developing highly active catalysts rather than facilitating oxygen transport.In this work,the oxygen transport behavior in CCLs based on highly active Fe-N-C catalysts is comprehensively explored through the elaborate design of two types of membrane electrode structures,one containing low-Pt-based CCL and NPMCbased dummy catalyst layer(DCL)and the other containing only the NPMC-based CCL.Using Zn-N-C based DCLs of different thickness,the bulk oxygen transport resistance at the unit thickness in NPMC-based CCL was quantified via the limiting current method combined with linear fitting analysis.Then,the local and bulk resistances in NPMC-based CCLs were quantified via the limiting current method and scanning electron microscopy,respectively.Results show that the ratios of local and bulk oxygen transport resistances in NPMCbased CCL are 80%and 20%,respectively,and that an enhancement of local oxygen transport is critical to greatly improve the performance of NPMC-based PEMFCs.Furthermore,the activity of active sites per unit in NPMCbased CCLs was determined to be lower than that in the Pt-based CCL,thus explaining worse cell performance of NPMC-based membrane electrode assemblys(MEAs).It is believed that the development of NPMC-based PEMFCs should proceed not only through the design of catalysts with higher activity but also through the improvement of oxygen transport in the CCL.

Data-driven prediction of temperature variations in an open cathode proton exchange membrane fuel cell stack using Koopman operator

In this study,a novel application of the Koopman operator for control-oriented modeling of proton exchange membrane fuel cell(PEMFC)stacks is proposed.The primary contributions of this paper are:(1)the design of Koopman-based models for a fuel cell stack,incorporating K-fold cross-validation,varying lifted dimensions,radial basis functions(RBFs),and prediction horizons;and(2)comparison of the performance of Koopman-based approach with a more traditional physics-based model.The results demonstrate the high accuracy of the Koopman-based model in predicting fuel cell stack behavior,with an error of less than 3%.The proposed approach offers several advantages,including enhanced computational efficiency,reduced computational burden,and improved interpretability.This study demonstrates the suitability of the Koopman operator for the modeling and control of PEMFCs and provides valuable insights into a novel control-oriented modeling approach that enables accurate and efficient predictions for fuel cell stacks.

PEMFC压差流道构型特征参数对电池性能的影响

针对质子交换膜燃料电池PEMFC(proton exchange membrane fuel cell)压差流道构型尺寸对电池电化学性能影响机理不明的问题,研究流道高度和脊背宽度对压差流道和直流道在氧气浓度、水浓度分布特征和电流密度、功率密度、压降等方面影响规律,并对两者进行了对比分析,结果表明流道高度对压差流道和直流道性能影响较小,压差流道在脊背宽度为1.25 mm和1.50 mm时具有明显优势;进一步研究压差流道变压区对流道性能的影响,结果表明变压区高度为0.05 mm和长度为1.50 mm时,压差流道峰值功率密度最高。综合考虑功率密度和压降的影响,选择压差流道高0.40 mm、宽1.25 mm、脊背宽1.25 mm、变压区长1.50 mm、高0.05 mm,此时压差流道峰值功率密度为0.3661 W/cm^(2),相较于直流道峰值功率密度提升6.3%。

PEMFC船形堵块阴极流场的性能

建立流体体积(VOF)两相流模型,研究船形堵块流道的排水性能。建立不同开孔率的船形堵块流道三维模型,研究船形堵块及开孔率对质子交换膜燃料电池(PEMFC)性能的影响。船形堵块流道峰值净功率密度相较于传统直流道可提升9.4%,相较于同堵塞率下的梯形堵块流道可提高2.9%,具有较好的强化传质作用。通过提高船形堵块流道的开孔率,PEMFC可以获得更好的性能。在相同开孔率下,船形堵块流道的氧气摩尔浓度较直流道和梯形堵块流道分别提高28.6%和14.0%。结果表明,相较于传统直流道,船形堵块流道可降低排水周期和流道内平均水含量,具有更好的排水性能。

基于NGO-CNN-BiLSTM神经网络的动态质子交换膜燃料电池剩余使用寿命预测

为解决质子交换膜燃料电池(PEMFC)剩余使用寿命(RUL)预测精度不高的问题,提出了一种基于北方苍鹰优化(NGO)、卷积神经网络(CNN)和双向长短时记忆(BiLSTM)神经网络的动态燃料电池RUL预测模型。首先,利用NGO对CNN-BiLSTM模型的学习率、隐藏节点及正则化系数进行寻优,然后,通过CNN-BiLSTM模型的卷积层对输入数据进行特征提取,输入到BiLSTM层进行时序建模和预测。同时,利用小波阈值去噪算法对原始数据进行平滑处理,采用皮尔逊相关系数提取模型输入变量,并搭建NGO-CNN-BiLSTM神经网络功率预测模型。仿真验证结果表明,该方法预测精度达99.49%,高于其他对比模型的预测精度。

Progress in the proton exchange membrane fuel cells(PEMFCs)water/thermal management:From theory to the current challenges and real-time fault diagnosis methods

Proton Exchange Membrane Fuel Cells(PEMFCs)are known as a promising alternative for internal combustion engines(ICE)to reduce pollution.Recent progress of PEMFCs is heading towards achieving higher power densities,reducing the refueling time,and decreasing the degradations,to facilitate the commercialization of hydrogen mobility.Model-assisted stack component development,diagnosis,and management are essential to ensure improved stack design and operation for tackling the existing implementation challenges of PEMFCs.Past reviews usually touched on a specific aspect,which can hardly provide the readers a complete picture of the key challenges and advances in water management.This paper aims at delivering a comprehensive source to review,from both experimental,analytical,and numerical viewpoints,the key operational challenges,and solutions of the stack to improve water/thermal management and cold start.In addition to presenting the fundamental theory to develop an analytical model,the recent advances in the flow field design,nanofluid coolants,and cold-start methods.Furthermore,the impacts of microstructural properties and the design of the porous layers on the water/thermal management are described.

基于IECSDE算法的PEMFC改进分数阶子空间辨识模型

为准确描述质子交换膜燃料电池(PEMFC)在其发电过程中的特性及变量影响关系,提出一种基于信息交流布谷鸟搜索差分进化(IECSDE)算法的改进分数阶子空间辨识方法来建立PEMFC分数阶模型。首先基于状态空间方程建立PEMFC模型,为了描述PEMFC的分数阶特性,将分数阶微分理论融入到模型中,引入Poisson滤波函数预处理实验数据,解决数据多阶不可导的问题,同时引入变步长记忆法处理分数阶微分时的权系数,提高子空间辨识精度。其次在辨识过程中的参数对于建模效果具有重大影响,因此基于IECSDE算法并对其进行优化,对布谷鸟搜索(CS)算法中的控制参数进行自适应处理,受到粒子群优化(PSO)算法的启发,改进随机游走方式提高收敛精度和速度,并引入差分进化(DE)算法与改进CS算法分别对种群进行优化,同时在寻优过程中进行信息交流提高种群的多样性和算法的鲁棒性。仿真结果表明,IECSDE算法的寻优能力在8种测试函数下比其他5种优化算法至少提升了10倍;通过对PEMFC测控平台收集到的实验数据进行模型辨识,所建立的模型将误差缩小到基于短记忆法的分数阶子空间辨识方法误差的20%,输出功率误差控制在0~0.1之间,输出电压误差控制在0~0.2之间,能够精准地模拟PEMFC发电过程。

Improved Semi-empirical Model of Proton Exchange Membrane Fuel Cell Incorporating Fault Diagnostic Feature

The membrane water content of the proton exchange membrane fuel cell(PEMFC)is the most important feature required for water management of the PEMFC system.Any improper management of water in the fuel cell may lead to system faults.Among various faults,flooding and drying faults are the most frequent in the PEMFC systems.This paper presents a new dynamic semi-empirical model which requires only the load current and temperature of the PEMFC system as the input while providing output voltage and membrane water content as its major outputs.Unlike other PEMFC systems,the proposed dynamic model calculates the internal partial pressure of oxygen and hydrogen rather than using special internal sensors.Moreover,the membrane water content and internal resistances of PEMFC are modelled by incorporating the load current condition and temperature of the PEMFC system.The model parameters have been extracted by using a quantum lightening search algorithm as an optimization technique,and the performance is validated with experimental data obtained from the NEXA 1.2 k W PEMFC system.To further demonstrate the capability of the model in fault detection,the variation in membrane water content has been studied via the simulation.The proposed model could be efficiently used in prognostic and diagnosis systems of PEMFC fault.

Ti_(4)O_(7) supported IrO_(x) for anode reversal tolerance in proton exchange membrane fuel cell

Fuel starvation can occur and cause damage to the cell when proton exchange membrane fuel cells operate under complex working conditions.In this case,carbon corrosion occurs.Oxygen evolution reaction(OER)catalysts can alleviate carbon corrosion by introducing water electrolysis at a lower potential at the anode in fuel shortage.The mixture of hydrogen oxidation reaction(HOR)and unsupported OER catalyst not only reduces the electrolysis efficiency,but also influences the initial performance of the fuel cell.Herein,Ti_(4)O_(7) supported IrO_(x) is synthesized by utilizing the surfactant-assistant method and serves as reversal tolerant components in the anode.When the cell reverse time is less than 100 min,the cell voltage of the MEA added with IrO_(x)/Ti_(4)O_(7) has almost no attenuation.Besides,the MEA has a longer reversal time(530 min)than IrO_(x)(75 min),showing an excellent reversal tolerance.The results of electron microscopy spectroscopy show that IrO_(x) particles have a good dispersity on the surface of Ti_(4)O_(7) and IrO_(x)/Ti_(4)O_(7) particles are uniformly dispersed on the anode catalytic layer.After the stability test,the Ti_(4)O_(7) support has little decay,demonstrating a high electrochemical stability.IrO_(x)/Ti_(4)O_(7) with a high dispersity has a great potential to the application on the reversal tolerance anode of the fuel cell.

金字塔状挡板影响PEMFC性能研究

质子交换膜燃料电池(PEMFC)流道结构主要影响气体流动、扩散和电化学反应。通过建立金字塔状流道挡板的PEMFC三维模型并进行数值模拟,探讨不同金字塔状挡板比率和挡板数量对燃料电池传质特性和输出性能的影响。结果表明:在流道内增添金字塔状挡板与无挡板流道相比,最大可提高气体垂直速度分量93.7%,进而提升气体由流道向催化层的传输性能;在金字塔状挡板比率为0.25,挡板数量为1时,燃料电池净功率最高可达到0.107 W。此外,增大挡板比率和增多挡板数量均可持续提高传质性能,但流道压降同时也会有最大18.5%的上升,使得PEMFC输出性能下降。