【作者】 詹跃东；

【导师】 王华； 朱建国；

【作者基本信息】 昆明理工大学 ， 冶金工程控制， 2010， 博士

【摘要】 在当前石油、天然气、煤等燃料紧张,电力供应不足,城市污染严重的情况下,燃料电池已经成为全球能源领域开发的热点。燃料电池是一种将持续供给的燃料和氧化剂中的化学能连续不断地转化为电能和热能的电化学装置,且没有中间的燃烧步骤。质子交换膜燃料电池(Proton Exchange Membrane Fuel Cell,简称PEMFC)由于具有功率密度高,能量转换率高、无污染、无噪音、低温条件下快速启动和可以实现零排放等优点,可作为便携式电子产品的移动电源,也可应用于中小型集中供电或分散式供电系统中,被称为21世纪的绿色环保能源,极具开发潜力和应用前景,是今后商业化前景最好的燃料电池。目前,PEMFC受到世界范围各国政府、研究机构和企业的重视,被列入未来世界十大科技之首。本论文是中国昆明理工大学和澳大利亚悉尼科技大学联合开发项目"PEMFC燃料电池的建模和控制研究”的主要部分。本论文研究的主要目的是为了提高PEMFC的输出特性,基于对PEMFC进行动态输出特性模型、动态气体传输模型、动态热传输模型和质子交换膜的水传输模型研究,提出有效的防止电池因控制因素导致性能衰减或失效的综合智能协调控制策略,并将PEMFC发电系统集成于不间断电源(UPS)中,作为移动电源系统及其产品开发。本论文的研究内容是在PEMFC输出特性影响因素的深入分析的基础上,对PEMFC热力学、反应动力学、质量与电荷传输、建模与控制和电池性能评价等方面进行理论研究,以及对PEMFC和UPS特性和模型参数的测量进行实验研究。由于PEMFC的输出性能依赖许多参数和因素,如氢气和氧气／空气的压力和流量、膜的温度和湿度以及化学计量比等等,所以,为了得到较好的PEMFC发电系统输出性能和温度特性,一些智能控制算法,如模糊控制、神经网络控制、预测控制和滑模变结构控制等,通过物理实现、实验测试和数字仿真等进行混合PEMFC-UPS电源系统的应用研究和试验。特别是将提出的综合智能协调控制策略应用于变化负载下的混合PEMFC-UPS电源系统中,通过相关实验研究,获得了满意的控制效果,具有一定的理论和应用价值。本论文的研究方法是首先设计开发了适用于千瓦级的PEMFC发电系统和UPS电源系统,作为混合PEMFC-UPS电源系统的实验装置。其次,分析了影响PEMFC输出特性的参数和因素,进行了影响因素分类研究,并提出了其输出性能的评价方法。然后,基于PEMFC发电系统的动态输出特性模型,为提高PEMFC输出特性和防止电池失效,提出了综合智能协调控制策略。另外,基于不精确的PEMFC动态热传输模型,进行了模糊自适应滑模变结构PEMFC温度控制和基于径向基(RBF)神经网络的模糊预测PEMFC温度控制的仿真实验研究。最后,实验和仿真结果验证了上述控制研究的可行性和正确性。本论文的主要工作和研究结果为：首先,基于采用成熟技术和产品开发形式的研究思想,设计了可用于千瓦级的PEMFC发电系统和UPS电源系统,组成了混合PEMFC-UPS电源系统实验装置,包括PEMFC、蓄电池(或超级电容器)、AC/DC整流器、DC/DC变换器、DC/AC逆变器和AC/DC充电器。为了降低成本,PEMFC选用自加湿式的空气冷却燃料电池,避免了PEMFC加湿系统的使用。设计的AC/DC整流器具有功率因数校正功能,减弱了由于整流滤波电路产生的谐波电流,提高了输入功率因数,可达到0.97以上,输入电流波形失真度(THD)小于5%。设计的DC/DC变换器选用推挽电路,其拓扑结构简单,与半桥电路和全桥电路相比,具有开关功率损耗较小,输出电压稳定和软启动等功能。设计的DC/AC逆变器,采用数字信号处理器(DSP) TMS320F240系列,实现了实时的数字控制,高速处理,对混合PEMFC-UPS电源系统实施智能网络化监控等功能。实验测试结果表明,设计的UPS电源系统的功率变换器是合理的和低成本。同时,实施的DC/AC逆变器的无差拍电压控制,明显地改善了UPS电源系统的输出电压波形失真度。第二,根据燃料电池控制机理和实验测试,研究了PEMFC运行过程中影响输出特性的因素和参数。根据对PEMFC的基本工作原理、关键技术、结构型式、材料选择、商品化进程以及在各个领域的应用过程进行全面分析结果,将PEMFC输出特性的影响参数和因素分为两大类：一类为控制参数,即对PEMFC输出特性的影响起直接作用的参数；另一类为非控制参数,即对PEMFC输出特性的影响起间接作用的参数,包括模型参数、物质传递参数、结构参数和材料参数等。而且,论文介绍了PEMFC的输出特性方程和模型,并提出了一种PEMFC输出特性的评价方法,通过稳态性能指标下的电流密度范围D和输出电压静差率S这两个指标可简单且方便地评价PEMFC的输出特性。第三,基于PEMFC的动态输出特性模型、动态气体传输模型、动态热传输模型和膜的水传输模型,为了提高PEMFC输出特性和防止电池失效,提出了混合PEMFC-UPS电源系统中的PEMFC发电系统的综合智能协调控制策略。当负载大幅度变化、尾气定时排放、电流中断在线测量膜的内电阻时,为了防止负载变化或压力变化造成的膜电极的泄漏和电堆的失效,采用智能专家控制策略,控制PEMFC和蓄电池之间的功率输出切换；为了防止发生燃料和空气缺失造成电堆的损坏,采用常规的PID控制策略,控制氢气燃料和空气的流量和压力；为了防止膜失水造成膜的热点击穿而损坏电堆,采用模糊自适应控制策略,控制电堆的温度。另外,设计的智能故障诊断专家系统辅助监测氢气燃料的流量和压力,电堆的温度、电流、电压以及膜的内阻等参数,并通过实验研究验证了提出的综合智能协调控制策略的可行性和正确性。第四,针对PEMFC动态热传输模型建立过程中存在的不精确性问题,为了提高PEMFC温度特性,应用了模糊自适应滑模变结构非线性控制算法控制电堆温度,并用MATLAB/SIMULINK工具和软件进行了仿真实验研究。引入模糊自适应控制算法,实现滑模切换控制中的切换速率和滑模等效控制中的反馈增益的自适应调节,减弱了滑模变结构系统引起的抖振影响,并维持了PEMFC运行过程的稳定性和动态性能。仿真实验结果表明,应用的控制算法既保持了滑模变结构控制的鲁棒性,又具有响应速度快、超调小、无静态误差等优点。最后,应用基于径向基(RBF)神经网络模糊预测控制算法进行了PEMFC温度控制的仿真实验研究。利用RBF神经网络进行了PEMFC温度模型的辨识,并采用模糊自适应的多步推理和性能测量方法计算性能评价指标,用模糊预测控制算法实施PEMFC的温度控制。因为通过对未来系统输出量的预测能达到对复杂过程的有效控制,所以,对PEMFC这样的非线性被控对象能获得较好的控制效果。应用MATLAB/SIMULINK软件的仿真实验结果表明,应用的控制方法能有效地实现PEMFC非线性系统的优化控制。更多还原

【Abstract】 Due to the shortage of the fossil fuels, such as the petroleum, natural gas, and mineral coal, the power under-supply, and serious urban pollution, the fuel cell technology has become a hot issue of research and development in the field of global energy. The fuel cell is an electrochemical device in which the sustainable supply of chemical energies in the fuel and oxidants can be continuously converted into electrical energy and heat energy, and has no intermediate combustion process. Because of the advantages of high power density, high energy conversion rate, no pollution, no noise, rapid start-up at low temperature, zero emission, and so on, the fuel cell can be taken as the mobile power system for portable electronic products, and applied in the middle and small size centralized power supply or distributed power system. The proton exchange membrane fuel cell (PEMFC) has been called as the environmental friently energy in the 21st century, which will have a profound developing potential and application prospect. Therefore, the PEMFC has been paid much attention to by many governments, research institutions and companies world wide, and has been listed in the top of 10 future technologies globally.My research task is from the major part of a project titled as "Modeling and Control of PEMFC Systems", which is jointly researched by the Kunming University of Science and Technology, China, and the University of Technology Sydney, Australia. The major objectives of this research project are to improve the output performance of PEMFC, prevent the failure of the stack, and develop numerical models, including PEMFC output performance model, dynamic gases transport model, dynamic thermal transport model, and dynamic water transport model in the membrane, and to present an effective comprehensive intelligent coordination control strategy preventing the PEMFC from the performance degradation because of the control factors, and to integrate the PEMFC generating system into UPS power systems, such as mobile power system and its product development.This research work includes theoretical study on thermodynamics, reaction kinetics, mass and charge transportation, modeling, control, and performance appraisal of the PEMFC based on a deep analysis of the PEMFC operational principles and its effecting factors, and experimental study on the measurement of model parameters and performance of the PEMFC and UPS. Since the performance of a PEMFC depends on a number of parameters, such as the pressure and mass flow rate of hydrogen and air/oxygen, the temperature and humidity of the membrane, and proportion of stoichiometry, etc., in order to obtain the best system performance, some intelligent control algorithms, such as the fuzzy logic, neural network, sliding model control, etc., have been studied and tested in UPS applications through physical implementation, experimental testing, and numerical simulation. The proposed comprehensive intelligent coordination control strategy has been employed in the integration of a practical PEMFC-UPS hybrid power system for variable electrical loads, by the related experimental investigations, the satisfied control results have been obtained, which is of important theory and application values.The research methods in this thesis are that it firstly designs and develops a kW-order PEMFC power system and UPS power system, which is taken as the experimental device of hybrid PEMFC-UPS power system. Secondly, the parameters and factors that affect the PEMFC output performance are analyzed, the classification study of affecting parameters is conducted, and an appraisal method of PEMFC output performance is proposed. Then, based on the PEMFC dynamic output voltage performance model, a comprehensive intelligent coordination control strategy is developed. On the other hand, based on the imprecise PEMFC dynamic thermal transfer model, simulation and experimental study of adaptive fuzzy sliding mode control strategy and fuzzy predictive control strategy based on radical basis function (RBF) neural network for PEMFC temperature control have been carried out. Finally, the experimental and simulation results are discussed, which have verified the feasibility and correctness of the above-mentioned control studies.The main contributions and achievements of this thesis work are given as follows:(1) Based on the research thoughts of adopting the matured techniques and the form of the products development, a kW-order PEMFC generating system and UPS power system have been designed, which consist of the experimental apparatus of PEMFC-UPS hybrid power system, such as PEMFC, batteries or supercapacitors, AC/DC rectifier, DC/DC converter, DC/AC inverter, and AC/DC charger. In order to reduce costs, a self-humidifying and air cooling PEMFC is selected, avoiding the use of the costly PEMFC humidifying system. The designed AC/DC rectifier is of the function of power factor correction (PFC), which greatly reduces the harmonic current generated by the rectifier and filter circuits, enhances the input power factor to more than 0.97, and makes the input current total harmonics distortion (THD) less than 5%. The designed DC/DC converter employs the push-pull circuit, which has simple topological structure and features lower switch power loss, more stable output voltage, softer start-up, etc., compared with the half-bridge circuit and full-bridge circuit. The designed DC/AC inverter uses digital signal process (DPS) TMS320F240 series, and releases the real-time numerical control, high-speed processing, and intelligent network monitoring for hybrid PEMFC-UPS power system. Experimental testing results show that the designed power converters for UPS power system are reasonable and low cost. Meanwhile, the implementation of dead-beat voltage control can obviously improve the waveform distortion of output voltage in UPS power system.(2) According to the control mechanisms and experimental testing of PEMFC, the parameters and factors affecting PEMFC output performance have been investigated during the operating process. In accordance with the complete analysis results of the basic operation principle, key technologies, structure types, material choice, commercial process, and application process in many fields of PEMFC, the affecting parameters and factors of PEMFC output performance are divided into two kinds of classifications:one is called as the control parameters, which play the direct roles of disturbing PEMFC output performance; the other is called as non-control parameters, which play the indirect roles of disturbing PEMFC output performance, including the model parameters, mass transfer parameters, structure parameters, material parameters, and so on. Moreover, this thesis has introduced the PEMFC output performance equations and model, and presented an evaluation approach for the PEMFC output performance, which can be easily evaluated by the proposed current density extent D and the steady-state error rate S of the steady-state performance indexes.(3) In the basis of the dynamic output model, dynamic gases transport model, dynamic thermal transfer model, and water transfer model in the membrane of PEMFC, a comprehensive intelligent coordination control strategy has been proposed for the PEMFC power system in the PEMFC-UPS hybrid power system. When the load changes sharply, the exhaust fixed-time discharges, the current is interrupted for on-line measuring the interior resistance of the membrane, in order to prevent the leakage of membrane electrode assembly (MEA) and the failure of the PEMFC stack, an intelligent expert control strategy is used to control the power output switching between the PEMFC and batteries. In order to prevent the starvation of the hydrogen and air that causes the damage of the stack, a conventional PID control strategy is applied to control the mass flow rate and pressure of the hydrogen and air. In order to prevent the dehydration of the membrane that leads to the hot breakdown and the damage of the stack, an adaptive fuzzy control strategy is employed to control the temperature of PEMFC. On the other hand, the designed intelligent troubleshooting expert system is used to auxiliary measure the parameters, such as the mass flow and pressure of hydrogen, the PEMFC’s temperature, current, and voltage, and the resistance of membrane. The experimental results have proved that the proposed comprehensive intelligent control strategy is the feasible and correct.(4) Aiming at the indiscernible problems in the process of building the dynamic heat transporting model of PEMFC and improving the temperature performance of PEMFC, an adaptive fuzzy sliding mode variable structure control algorithm is applied to control the PEMFC temperature, and simulation has been done using the MATLAB/SIMULINK tool and software. By introducing the adaptive fuzzy control method, the switch rate in the sliding mode switch control and feedback gains in the sliding mode equivalent control can be adaptively adjusted, which can reduce the chattering effects caused by the sliding mode variable structure control, and keep the stability and dynamic properties. The simulation and experimental results show that the employed control algorithm can not only keep the robustness of sliding mode variable structure control, but also is of the advantages of fast responding speed, smaller overshoot, no steady-state error, etc.(5) Using the fuzzy predictive control algorithm based on the RBF neural network, the simulation study for the PEMFC temperature control has been done. RBF neural network is used to identify the model of PEMFC temperature performance, and the multiple inference and performance measuring method of adaptive fuzzy are applied to calculate the performance evaluation index, and then the fuzzy predictive control algorithm is employed to realize the PEMFC temperature control. Through predicting the output of future system, the effective control for the complex process can be realized, and the nonlinear plants like PEMFC can obtain better control effect. Using the MATLAB/SIMULINK tool, the simulation results indicate that the control method applied can effectively realize the optimal control for the PEMFC nonlinear system.更多还原