阴极开放式质子交换膜燃料电池实验性研究

文中围绕实验室自制的开放式阴极自增湿型质子交换膜燃料电池开展了大量相关实验,采用FLUKE Ti25红外温度成像仪测得了各种操作条件下电池表面温度分布图像。实验结果表明:在封闭式阳极(anode dead-end)操作条件下,液态水会在阳极逐渐积累而影响反应气的传质,造成电池输出性能的衰减。通过阳极排气可以使电池性能恢复。纵观电堆表面温度分布情况,总体呈现出沿氢气流道方向递增的趋势。且随着电流密度的增大,这种温度分布的不均匀性变得更加明显。在实验所测试的范围内,电堆的平均输出功率密度达到了583 mW/cm2。     

质子交换膜燃料电池的应用研究

质子交换膜燃料电池（PEMFC）与其它燃料电池一样，是利用氧化、还原反应产生电子流的装置。它以氢为燃料、以氧为氧化剂，把化学能直接转化为电能。由于该电池以氢气为燃料，生成的产物是水，对环境造成的污染少。在化石燃料日益短缺及环境污染日益严峻的条件下，燃料电池倍受关注。而近几年发展起来的质子交换膜燃料电池（PEMFC）由于其无污染、发电效率高等特点正受到各国各部门的重视。主要评述了PEMFC的主要用途、工作原理及其实现商业化所面临的几个主要问题。     

质子交换膜燃料电池

因其具有独特的优点，质子交换膜燃料电池（PEMFC）的市场前景很好，国际上已经形成了一股研究开发热潮。电催化剂、质子交换膜、双极板、燃料、水管理、热管理是质子交换膜燃料电池的关键技术。文章介绍了PEMFC的特点及开发应用状况，综述了PEMFC的研究进展。     

质子交换膜燃料电池的研发动态

质子交换膜燃料电池(PEMFC)因其独特的优点具有很好的市场前景,国际上已经形成了一种研究热潮.电催化剂、质子交换膜、双极板、燃料、水管理、热管理是其关键技术.文章介绍了PEMFC的特点及开发应用状况,综述了PEMFC的研究进展.     

质子交换膜燃料电池发电系统控制策略研究

质子交换膜燃料电池堆(PEMFC)的操作温度和压力对发电系统的输出性能有着显著的影响,因此针对电堆温度和压力控制的研究也就成为一项重要的课题.介绍了PEMFC的工作原理和系统结构,分析了电堆温度与压力的变化特性和控制策略,提出了多种控制方案,并进行优缺点比较.     

基于T-S模型的质子交换膜燃料电池控制建模

对PEMFC非线性复杂被控对象,提出了一种在线辨识模糊预测算法,用模糊聚类和线性辨识方法在线建立PEMFC控制系统的T—S模糊预测模型,仿真实验结果表明了该模糊辨识建模方法具有建模简单、模型精度高等优点,亦证明了该算法的有效性和优越性。研究结果对质子交换膜燃料电池控制系统的建模和控制具有一定的实用价值。     

质子交换膜燃料电池发电系统设计

从军事领域对燃料电池技术的需求进行了分析、说明,针对军事应用需求,着重介绍了某项目氢燃料电池发电系统及其主要组成部分:电堆、供氢子系统、空气供给子系统、水热管理子系统等的技术方案,并对系统主要参数进行了匹配设计计算.根据设计方案,建立了系统性能仿真模型,对系统性能进行了仿真预测研究,结果基本满足预期目标.     

质子交换膜燃料电池的膜电极及其湿度特性

质子交换膜燃料电池的膜电极结构与电池性能密切相关，膜的湿度直接影响膜的性能。膜内水的迁移受到多个参数的影响：较大的电流密度使水的净迁移量下降；电池温度的提高将增大电池水平衡的电流密度；提高湿化程度可以减小膜的欧姆损失。膜内的湿度不足以保证燃料电池正常工作，就必须采用湿化方法。水的迁移过程涉及到电池的压降和温度变化。实际的湿度状态是各种因素的综合．电池的工作条件最终决定了它自身的水平衡状态。     

质子交换膜燃料电池可靠性分析

可靠性是质子交换膜燃料电池(PEMFC)的重要指标，文中定性分析了PEMFC组成元件、装配工艺和工作过程的可靠性。提出了提高PEMFC可靠性的措施和可靠性的设计原则。     

质子交换膜燃料电池故障检测研究

针对质子交换膜燃料电池(PEMFC)发电系统的故障检测和系统稳定性问题,结合其多传感器特性,采用基于实时PCA的质子交换膜燃料电池故障检测方法,根据燃料电池反应信号数据建立PCA模型,通过窗口过滤方式和遗忘因子算法实时更新模型,并将降维后获得的数据用统计方法进行处理,从而检测出故障。有效地简化了燃料电池系统故障检测的过程,改善了故障检测的实时性,提高了燃料电池系统工作的稳定性和可靠性。     

A cold start mode of proton exchange membrane fuel cell based on current control

In this study, a mathematical model is established to simulate the cold start of fuel cell, including the calculation of the temperature distribution and heat exchange. Moreover, a novel cold-start mode is designed and compared with the constant and linear current cold-start modes. It uses the ice volume and heat absorbed by the membrane as fuzzy control inputs and outputs current density. Compared with other modes at 263 K, the cold startup time is shortened by 25.6–41.6 s, and the ice volume fraction is reduced by 29.4%–31.8%. Only the proposed mode achieves a successful cold start at a lower temperature. Also, the proposed mode has better thermal behavior, as indicated by the temperature distribution diagrams. Furthermore, to avoid performance degradation caused by cold starts, an inertia link is added to the controller, so that the current amplitude is reduced by 7.98%, and the maximum change rate by 57.44%.     

Weighted fusion control for proton exchange membrane fuel cell system

Oxygen excess ratio (OER) is closely correlated with the power generation efficiency and dynamic performance of proton exchange membrane fuel cell (PEMFC) system. As OER changes with varying load, it is prone to oxygen starvation and slow response to OER reference value, and great challenges to OER control technology are brought. To this end, a dual closed-loop weighted fusion control for PEMFC system is proposed. The outer loop is utilized to obtain the optimal OER reference value, and the inner loop is utilized to track the OER reference value. This inner loop combines the merits of active disturbance rejection control (ADRC) algorithm and fuzzy self-tuned PID (FSTPID) method. Simulation results reveal that the proposed approach is superior to the other three methods in reducing the overshoot, settling time and avoiding oxygen starvation issues, and also in improving several key performance indices, such as integrated absolute error, settling time, etc.     

Dynamic modeling of proton exchange membrane fuel cell using non-integer derivatives

The modeling of proton exchange membrane fuel cells (PEMFC) may work as a powerful tool in the development and widespread testing of alternative energy sources in the next decade. In order to obtain a suitable PEMFC model, which can be used in the analysis of fuel cell-based power generation systems, it is necessary to define the values of a specific group of modeling parameters. In this paper, the authors propose a dynamic model of PEMFC, the originality of which lays on the use of non-integer derivatives to model diffusion phenomena. This model has the advantage of having least number of parameters while being valid on a wide frequency range and allows simulating an accurate dynamic response of the PEMFC.

In this model, the fuel cell is represented by an equivalent circuit, whose components are identified with the experimental technique of electrochemical impedance spectroscopy (EIS). This identification process is applied to a commercially available air-breathing PEMFC and its relevance is validated by comparing model simulations and laboratory experiments. Finally, the dynamic response derived from this fractional model is studied and validated experimentally.     

Dynamic modeling and simulation of air-breathing proton exchange membrane fuel cell

Small fuel cells have shown excellent potential as alternative energy sources for portable applications. One of the most promising fuel cell technologies for portable applications is air-breathing fuel cells. In this paper, a dynamic model of an air-breathing PEM fuel cell (AB-PEMFC) system is presented. The analytical modeling and simulation of the air-breathing PEM fuel cell system are verified using Matlab, Simulink and SimPowerSystems Blockset. To show the effectiveness of the proposed AB-PEMFC model, two case studies are carried out using the Matlab software package. In the first case study, the dynamic behavior of the proposed AB-PEMFC system is compared with that of a planar air-breathing PEM fuel cell model. In the second case study, the validation of the air-breathing PEM fuel cell-based power source is carried out for the portable application. Test results show that the proposed AB-PEMFC system can be considered as a viable alternative energy sources for portable applications.     

Multivariable robust control of a proton exchange membrane fuel cell system

This paper applies multivariable robust control strategies to a proton exchange membrane fuel cell (PEMFC) system. From the system point of view, a PEMFC can be modeled as a two-input-two-output system, where the inputs are air and hydrogen flow rates and the outputs are cell voltage and current. By fixing the output resistance, we aimed to control the cell voltage output by regulating the air and hydrogen flow rates. Due to the nonlinear characteristics of this system, multivariable robust controllers were designed to provide robust performance and to reduce the hydrogen consumption of this system. The study was carried out in three parts. Firstly, the PEMFC system was modeled as multivariable transfer function matrices using identification techniques, with the un-modeled dynamics treated as system uncertainties and disturbances. Secondly, robust control algorithms were utilized to design multivariable H_∞ controllers to deal with system uncertainty and performance requirements. Finally, the designed robust controllers were implemented to control the air and hydrogen flow rates. From the experimental results, multivariable robust control is shown to provide steady output responses and significantly reduce hydrogen consumption.     

Semi-analytical proton exchange membrane fuel cell modeling

Mathematical techniques are presented which allow for analytical solutions of the catalyst layer transport and electrochemical problem in PEM fuel cells. These techniques transform the volumetric reaction terms to boundary flux terms, thereby eliminating the need for computational solving of the catalyst layer problem. The result is a semi-analytical fuel cell model—a computational model that entails analytical rather than computational catalyst layer solutions. This helps to alleviate the meshing difficulties inherent in the catalyst layers caused by large geometric aspect ratios, and hence reduce the computational requirements for fuel cell models.     

Dynamic modeling of a high-temperature proton exchange membrane fuel cell with a fuel processor

A dynamic model of a high-temperature proton exchange membrane fuel cell with a fuel processor is developed in this study. In the model, a fuel processing system, a fuel cell stack, and an exhaust gas burner are modeled and integrated. The model can predict the characteristics of the overall system and each component at the steady and transient states. Specifically, a unit fuel cell model is discretized in a simplified quasi-three-dimensional geometry; therefore, the model can rapidly predict the distribution of fuel cell characteristics. Various operating conditions such as the steam-to-carbon ratio, oxygen-to-carbon ratio, and autothermal reforming inlet temperature are varied and investigated in this study. In addition, the dynamic characteristics exhibited during the transient state are investigated, and an efficiency controller is developed and implemented in the model to maintain the electrical efficiency. The simulation results demonstrate that the steam-to-carbon ratio and the oxygen-to-carbon ratio affect the electrical and system efficiency and that controlling the fuel flow rate maintains the electrical efficiency in the transient state. The model may be a useful tool for investigating the characteristics of the overall system as well as for developing optimal control strategies for enhancing the system performance.     

Modelling of proton exchange membrane fuel cell performance based on semi-empirical equations

Using semi-empirical equations for modeling a proton exchange membrane fuel cell is proposed for providing a tool for the design and analysis of fuel cell total systems. The focus of this study is to derive an empirical model including process variations to estimate the performance of fuel cell without extensive calculations. The model take into account not only the current density but also the process variations, such as the gas pressure, temperature, humidity, and utilization to cover operating processes, which are important factors in determining the real performance of fuel cell. The modelling results are compared well with known experimental results. The comparison shows good agreements between the modeling results and the experimental data. The model can be used to investigate the influence of process variables for design optimization of fuel cells, stacks, and complete fuel cell power system.     

Dynamic modeling and adaptive control of voltage in proton exchange membrane fuel cell using water management

Maintaining a constant voltage in polymer electrolyte membrane fuel cells (PEMFCs) has always attracted the attention of many researchers, and many articles have been published on this issue. Furthermore, water management in PEMFC has become an important challenge because it can improve cell efficiency and lifetime. This paper will develop a one‐dimensional dynamic model for a single PEMFC, which correlates changes in the cell voltage to changes in the cell current density and humidification rate. Subsequently, a recurrent neural network controller based on the approximation of nonlinear autoregressive moving average model is proposed. The controller manipulates the anode and the cathode water mole fractions in order to fix cell voltage and preserve cell water content within a satisfactory interval regardless of the varying cell current. The model and the controller are simulated in matlab /Simulink (Mathworks Inc., Natick, MA) software, and the results are compared with a PID controller from different viewpoints such as current disturbance and plant parameter variation. Copyright © 2011 John Wiley & Sons, Ltd.