Intelligent Modelling, Optimization And Control Of Proton Exchange Membrane Fule Cells Generation System

The problem of energy shortage is the world development confronted. Good environment performance of high power efficiency, high reliability, lower noisy, zero-exclusion has quickly made the PEMFC appropriate energy conversion device for solving the energy problem in 21th century.The character Proton Exchange Membrane Fuel Cell (PEMFC) which has of fast startup, drainage convenient and high power, high efficient energy conversion made it especially for electric vehicle, mobile power source, and distributed power station .It is new type of general power source for army and civilian and has good future of commercialization .The study background of this dissertation is just based on the above virtue and problem.With the gradually maturation of PEMFC technology and cosmically commercialization, better performance has been put forward for its reliability and high efficiency. In addition to the manufacture technics of the fuel cell, the performance of the control system is very important. Control system adjusts the flow rate of the react gas parameter according to the actual running condition and the required power for the correspond load so as to ensure the efficiency of electrochemical react. At the present, the research is mainly focused on the mechanism model, structure and material in world. The reliability and efficiency of the fuel call stack can be improved by the control system.The object of control system design is to ensure the stabilization of the fuel cell work temperature and pressure to ensure the fuel cell good output performance.By optimization the running operation parameter to maintain the reliability and security running enviorment for the fuel cell. However, these aspects are in weak study of the PEMFC development. Thus further study needs us to do for the control oriented model, optimization and control strategies of PEMFC.The task of the project is combined with"ten five"national defence scientific research item -the vehicle with 20kW PEMFC drive system of and"Kilowatt PEMFC stack power system development" "985 Project"items being researched in the institute of the fuel cell Shanghai JiaoTong university. The dissertation quantitative analysis many factors affected the PEMFC performance and analysis the PEMFC system model and build up the simulation model, inorder to maintain desired level,the dynamic feedforward controller and PI controller has been adopted to achieve the desired FC system net power. In order to avoid the severe cases of the short circuit and a hot spot on the surface of a membrane cell that caused by oxygen starvation, we proposed the disturbance observer based control for the PEMFC generation system. we give the procedure of designing the nonlinear disturbance observer and compositing the nonlinear disturbance observer to the controller. The paper proposed the particle swarm optimization searching method for the parameter of PID controller of the nonlinear disturbance observer based control of the PEMFC system, and test the effectiveness of this algorithm by comparing it with GA based method. By feedforward compensation of the estimated stack current yielded by the disturbance observer, the steady-state performance and the disturbance attenuation ability of the PEMFC system was significantly improved. To avoid the oxygen starvation when current is drawn from the fuel cell and to guarantee the fuel cell can work near the effective operating point when transient and high current occur, we adopt nonlinear model predictive control. to model the oxygen stoich in cathode. The paper has studied the support vector machine regression modeling theory based on statistic theory, particle swarm optimization and smart predictive control. Then constructs the SVMR model of oxygen stoich of PEMFC and adopts the smart predictive control for the oxygen stoich of PEMFC, and chooses the SVMR model as the predictive model, receding optimization method is adopt the particle swarm optimization, and compares the control effectiveness with the GA based receding optimization by simulation, validate better control effectiveness of the proposed the smart predictive control.The main contributions and achievements are given below:(1) According to the experimental model and the outside observed data of fuel cell,the paper analysis effects of the operation parameter, the proton exchange memeberane and the electric current on the output performance of fuel cell. And then analysis the assemble of the fuel cell and wrong operation affects on the life of fuel cell.Then give the conclusion of the challenge to improve the PEMFC performance.The results lay for the regulation the operation parameter of PEMFC , improvement the system output performance and also lay the basis for the system design and dynamic analysis.(2) The thesis analysis the principle of the parts of the PEMFC power generation system and build their simulation model. Inorder to make the fuel cell power generation system arrive good disturbance rejection performance, and to get the designed net output power, we adopts the dynamic feedforward controller and PI feedback controller to control the level of the oxygen stoich in the cathode.(3) It needs to regulate the oxygen depleted from the fuel cell cathode during power generation of the air supply subsystem of FC. This regulation needs to be achieved fast and efficiently to avoid oxygen starvation and extend the life of the fuel cell stack. Inorder to avoid the severe cases of the short circuit and a hot spot on the surface of a membrane cell that caused by oxygen starvation, we proposed the disturbance observer based control for the PEMFC generation system. we give the procedure of designing the nonlinear disturbance observer and compositing the nonlinear disturbance observer to the controller.(4) The paper proposed the searching optimal method for the parameter of pressure PID controller based on particle swarm optimization of the nonlinear disturbance observer based control of the PEMFC system, and test the effectiveness of this algorithm by comparing it with GA based method. The global exponential stability of the proposed disturbance observer is guaranteed by selecting design parameters, which depend on the maximum of the oxygen stoichiometric excess and operation conditions of PEMFC systems. The performance of the proposed observer is demonstrated by tracking the excess oxygen ratio while the disturbed current vary. The composite controller improves disturbance attenuation ability of the PEMFC system. Both experimental and simulation results show the disturbance observer works well. By feedforward compensation of the estimated stack current yielded by the disturbance observer, the steady-state performance of the PEMFC system was significantly improved.(5) To avoid the oxygen starvation when current is drawn from the fuel cell and to guarantee the fuel cell can work near the effective operating point when transient and high current occur, we adopt nonlinear model predictive control. to model the oxygen stoich in cathode, and construct the SVMR model of the oxygen stoich in cathode ,then verify the model satisfy the need for the predict control , and lay for the predict control. The thesis first proposed to adopt the smart predictive control for the oxygen stoich of PEMFC, and choose the SVMR model as the predictive model, receding optimization method is adopt the particle swarm optimization, and compare the control effectiveness with the GA based receding optimization by simulation, validate better control effectiveness of the proposed the smart predictive control. Then proposed three different smart predictive controller structure based on different control criterions and compare their advantage.