固体氧化物燃料电池的现状与发展

固体氧化物燃料电池是将燃料中的化学能直接转化为电能的电化学装置，具有高效率、零污 染、无噪声等特点。它可以为民用、商业、军事和交通运输等提供高质量的电源。这一技术 的成功应用对于缓解能源危机、满足对电力数量和质量的需求、保护生态环境和国家安全都 具有重大的意义。本文简略地介绍了固体氧化物燃料电池及其现状和存在的问题，并就作者 的观点提出了值得深入研究的课题。     

基于文献计量的固体氧化物燃料电池技术发展研究

利用Science Citation Index Expanded（SCIE）数据库相关文献数据,运用文献计量法、合著网络分析以及文本分类法,系统分析了SOFC技术的发展趋势、国家合作倾向、研发热点等内容。结果显示,国家间合作有明显倾向性与地缘性,研发重心逐渐从美日等发达国家向中印等发展中国家转移;混合系统设计、电解质薄膜制造等研究热点可能是推动SOFC技术产业化的关键。最后,提出探索适合我国应用场景的技术路线、深化国际合作以及加强SOFC创新链部署等建议。     

A review on high power SOFC electrolyte layer manufacturing using thermal spray and physical vapour deposition technologies

Manufacturing of solid oxide fuel cell （SOFC） components remains nowadays a key point for the indus- trial development of this technology. Especially, the deposition of the dense electrolyte layer which is sand- wiched between the porous anode and the porous cathode is of paramount importance and thus focuses a lot of attention. Therefore, this paper considers and reviews recent developments concerning solid electrolyte layers manufacturing using thermal spray （TS） and physical vapour deposition （PVD） technologies.     

SOFC temperature evaluation based on an adaptive fuzzy controller

The operating temperature of a solid oxide fuel cell （SOFC） stack is a very important parameter to be controlled, which impacts the performance of the SOFC due to thermal cycling. In this paper, an adaptive fuzzy control method based on an affine nonlinear temperature model is developed to control the temperature of the SOFC within a specified range. Fuzzy logic systems are used to approximate nonlinear functions in the SOFC system and an adaptive technique is employed to construct the controller. Compared with the traditional fuzzy and proportion-integral-derivative （PID） control, the simulation results show that the designed adaptive fuzzy control method performed much better. So it is feasible to build an adaptive fuzzy controller for temperature control of the SOFC.     

Iterative learning control of SOFC based on ARX identification model

This paper presents an application of iterative learning control (ILC) technique to the voltage control of solid oxide fuel cell (SOFC) stack. To meet the demands of the control system design, an autoregressive model with exogenous input (ARX) is established. Firstly, by regulating the variation of the hydrogen flow rate proportional to that of the current, the fuel utilization of the SOFC is kept within its admissible range. Then, based on the ARX model, three kinds of ILC controllers, i.e. P-, PI- and PD-type are designed to keep the voltage at a desired level. Simulation results demonstrate the potential of the ARX model applied to the control of the SOFC, and prove the excellence of the ILC controllers for the voltage control of the SOFC.     

Predictive control of a direct internal reforming SOFC using a self recurrent wavelet network model

In this paper, an application of a nonlinear predictive controller based on a self recurrent wavelet network （SRWN） model for a direct internal reforming solid oxide fuel cell （DIR-SOFC） is presented. As operating temperature and fuel utilization are two important parameters, the SOFC is identified using an SRWN with inlet fuel flow rate, inlet air flow rate and current as inputs, and temperature and fuel utilization as outputs. To improve the operating performance of the DIR-SOFC and guarantee proper operating conditions, the nonlinear predictive control is implemented using the off-line trained and on-line modified SRWN model, to manipulate the inlet flow rates to keep the temperature and the fuel utilization at desired levels. Simulation results show satisfactory predictive accuracy of the SRWN model, and demonstrate the excellence of the SRWN-based predictive controller for the DIR-SOFC.     

钙钛矿型复合氧化物的结构分析及其在SOFC阴极中的应用

对钙钛矿型复合氧化物（ABO3）的结构特征和性质进行详细分析,研究表明,以合适的阳离子取代A、B位离子而形成含有氧空穴的钙钛矿结构是钙钛矿型复合氧化物演变为各种功能材料的基础。通过适当的掺杂,钙钛矿型复合氧化物可同时具有良好的导电性、催化活性、热稳定性和化学稳定性,因此在SOFC中有广泛的应用。分别以LSM、LSCF等典型钙钛矿型复合氧化物为例,阐述了钙钛矿型复合氧化物在SOFC阴极中的应用。     

基于遗传算法优化最小二乘支持向量回归机的平板型固体氧化物燃料电池的控制相关动态辨识建模

研究目的：为了同时预测固体氧化物燃料电池（SOFC）的电压、温度动态特性和设计控制器,建立SOFC的控制相关动态辨识模型。创新要点：为了建立SOFC更精确的最小二乘支持向量回归机（LSSVR）动态模型,采用遗传算法（GA）优化LSSVR的参数。所建GA-LSSVR模型可同时预测SOFC的电压和温度动态特性。研究方法：1.分析SOFC的电化学和能量平衡子模型。2.利用所选择的最优LSSVR参数,建立了SOFC的GA-LSSVR动态辨识模型。通过仿真分析和比较,验证了所建模型的有效性（图3和4）。3.利用所建模型的预测结果,与模拟退火算法优化最小二乘支持向量回归机（SAA-LSSVR）和5折交叉验证最小二乘支持向量回归机（5FCV-LSSVR）模型的预测结果进行了比较,表明所建立的GA-LSSVR模型具有较高的预测精度（表3和4）。重要结论：通过比较SAA-LSSVR和5FCV-LSSVR模型的预测结果,发现所建GA-LSSVR模型具有较好的预测性能和精度。基于所建立的GA-LSSVR模型可进行有效的多变量控制器设计。     

Numerical simulation of a direct internal reforming solid oxide fuel cell using computational fluid dynamics method

A detailed mathematical model of a direct internal reforming solid oxide fuel cell （DIR-SOFC） incorporating with simulation of chemical and physical processes in the fuel cell is presented. The model is developed based on the reforming and electrochemical reaction mechanisms, mass and energy conservation, and heat transfer. A computational fluid dynamics （CFD） method is used for solving the complicated multiple partial differential equations （PDEs） to obtain the numerical approximations. The resulting distributions of chemical species concentrations, temperature and current density in a cross-flow DIR-SOFC are given and analyzed in detail. Further, the influence between distributions of chemical species concentrations, temperature and current density during the simulation is illustrated and discussed. The heat and mass transfer, and the kinetics of reforming and electrochemical reactions have significant effects on the parameter distributions within the cell. The results show the particular characteristics of the DIR-SOFC among fuel cells, and can aid in stack design and control.     

H2S／air固体氧化物燃料电池的性能研究

采用陶瓷薄膜技术及溶胶一凝胶法制备了氧离子传导YSZ（Y2O3稳定的ZrO2）电解膜与电极催化剂,构建了膜电极组装（MEA）及结构为H2S、（复合MoS2阳极）／YSZ传导膜／（复合NiO阴极）、空气燃料电池系统;通过在MoS2中掺杂NiS、电解质、Ag粉和淀粉制备了双金属复合MoS2阳极催化剂,在NiO中添加电解质、Ag粉和淀粉制备了复合NiO阴极催化剂：考察了不同操作温度对电池性能的影响,比较了几种不同电极催化剂的性能,研究了H2S／air固体氧化物燃料电池的电化学性能。实验结果表明,在H2S环境中,复合MoS2阳极催化剂比MoS2和Pt具有更好的性能,复合Nio阴极Pt阴极的极化小;在电极催化剂中加入Ag可显著提高电极的导电性．添加电解质和淀粉可以提高电极的离子传导性和多孔性：操作温度增加．传导膜的电传导率和电化学反应速率增加,电池的输出电流与功率密度增加,电化学性能变好。电池连续运行1～4d几乎不降级。在850℃和101．13kPa时．燃料电池最大输出功率密度为155mW·cm^-2,对应的电流密度为240mA·cm^-2。