Research On Performance Optimization And Fault-tolerant Control Method Of PEMFC Power Generation System

With the development goals of "carbon peak" and "carbon neutrality",new energy has become an inevitable trend in the development of my country’s and even the global energy industry.Proton Exchange Membrane Fuel Cell(PEMFC)is characterized by its high efficiency,The advantages of non-polluting,low noise,and not being restricted by the Carnot cycle have attracted widespread attention from countries all over the world.In order to realize the wider application of PEMFC power generation system,in addition to increasing investment in research on new materials with high performance and low cost,it is also indispensable to implement research work at the system control level.However,most of the existing researches focus on the optimization of the operation of the system under normal conditions,and do not consider the influence of factors such as the perturbation of the internal parameters of the stack,the complex and changeable external operating environment,and the failure of key components accompanying the operation of the system.This paper mainly studies the modeling,system performance optimization control and fault-tolerant control method of PEMFC power generation system.The main research results are as follows:(1)The PEMFC power generation system model is established,in which the air compressor model adopts the mechanism model to replace the classical data fitting model,and the influence of environmental changes on the air compressor flow supply characteristics is analyzed.A hardware-in-the-loop test platform based on RT-LAB is built,and the model is verified in the hardware-in-the-loop mode,which provides a basis for the study of optimal control methods in the following chapters.(2)Aiming at the influence of environmental changes on system operating characteristics,a net power optimization control method of PEMFC power generation system based on extreme value search is proposed.This method studies the influence factors of the environment on the operating characteristics of the PEMFC power generation system,adopts the extreme value search strategy to optimize the optimal peroxide ratio online,and combines the model-free based on compact form dynamic linearization(CFDL).The self-adaptive control strategy realizes the tracking of the optimal oxygen excess ratio(OER)under the change of altitude environment.Based on the hardware-in-the-loop platform,it is verified that the proposed method can realize the adaptive adjustment of the optimal peroxygen ratio in different operating environments,and ensure the maximum output of the net power of the system.(3)Aiming at the dynamic response of PEMFC power generation system under external disturbance and internal parameter perturbation,a disturbance suppression method for PEMFC power generation system based on active disturbance rejection-sliding mode control is proposed.The inner loop of the method uses the Active Disturbance Rejection Control(ADRC)strategy to observe and compensate the disturbance,which offsets the influence of the unknown disturbance.The outer loop designs the Super-twisting sliding mode control strategy according to the Lyapunov stability principle..Based on the hardware-in-the-loop platform,the effectiveness of the proposed method is verified by comparative analysis under three operating conditions: normal operating state,external disturbance and parameter perturbation.(4)Aiming at the operation failure of the gas supply subsystem of the PEMFC system,a fault-tolerant control method of the PEMFC power generation system based on the Strong Tracking Filter(STF)is proposed.In this method,the fault of the air flow meter and the fault of the gas supply pipeline are estimated by designing a strong tracking filter,and the oxygen excess ratio is reconstructed in combination with the estimation results.(Generalized Predictive Control,GPC)oxygen excess ratio control strategy.Based on the hardware-in-theloop platform,it is verified that the proposed method can effectively maintain the oxygen excess ratio near the set value in the event of failure.