Study On Comprehensive Intelligent Coordination Control Of Proton Exchange Membrane Fuel Cell

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.