Modeling And Control Of High Temperature Solid Oxide Fuel Cells

As one kind of new power plants,solid oxide fuel cell(SOFC)possesses distinctive advantages,such as the high efficiency in energy conversion,the tiny effect towards environmental pollution,and the abundant fuel sources,etc.Nevertheless,the drastic chemical reactions inside and the high operating temperature(up to 1000℃)lead to a series of problems in structural analysis,controller design as well as safety guarantee of SOFC.Therefore,how to improve the operational efficiency and stability of SOFC has been a research hotspot and difficulty in recent years.The sealed space and multifarious process make that the system suffers from various uncertainties and nonlinearities inevitably,for example,uncertainty of the internal parameters of SOFC,the effect of temperature on the methane conversion rate in the reaction kinetics model of methane steam reforming(MSR)is non-linear,and the effect of hydrogen flow velocity on the output voltage of the battery in the electrochemical model of hydrogen oxygen reaction(HOR)is also non-linear.so the conventional control methods depending seriously on the modeling accuracy are inefficient and unreliable for the process control of reactions.However,iterative learning control(ILC)can deal with highly uncertain dynamic systems in a very simple way,and requires only a small amount of prior knowledge and computation.At the same time,it is highly adaptive and easy to realize.In this paper,the ILC method is used for the precise control of SOFC systems.The details are as follows:Firstly,according to the working principle of SOFC,the dynamic modeling of the MSR reaction inside SOFC was carried out,and the influence of some parameters in the model on the methane conversion rate was preliminarily analyzed through the model and experimental data.Then two ILC schemes were proposed for the precise management of the efficiency of methane conversion in SOFC,where distinctive scenarios with respect to different input variables,namely,the reaction temperature for the single-input system as well as the velocity ratios of steam and nitrogen to carbon for multi-input system,are considered respectively.Furthermore,the learning convergence condition of ILC,the learning rate as well as the robustness are addressed through rigorous analysis.The simple structure and model-free nature of ILC makes it applicable although the MSR process is with complicated dynamics and severe potential uncertainties.The effectiveness of the proposed ILC schemes is confirmed via numerical simulations.At last,HOR electrochemical model was established through Nernst equation,and ILCcontroller was designed according to the characteristics of the model.Simulation results show the effectiveness of the ILC algorithm and the exact control of SOFC output voltage.The results show that because SOFC is an electrochemical cycling system,the internal reactions are always repeated,and the entire control system presents a clear repeatable kinetics.ILC is an inherent control method of SOFC dynamics model,which improves the current input signal through previous experimental information and finally gets the desired output result.Therefore,we can use the ILC method to design controllers for SOFC systems,and ultimately achieve the purpose of improving SOFC operating efficiency and stability.