Root Cause Diagnosis And Control Of Solid Oxide Fuel Cell System Oscillations Based On Data And Model

Solid oxide fuel cell(SOFC)system is a device that uses fuel to generate electricity.It has the advantages of low emissions,high efficiency,and long life.However,the occurrence and propagation of oscillations are common in a system.When certain variables oscillate,the lifetime of system is significantly reduced and the output electrical characteristics are affected.Therefore,it is important to analyze,diagnose and control the root cause of SOFC system oscillations to prevent oscillations from causing adverse effects on the system.An independent SOFC system consists of multiple subsystems,and each subsystem consists of multiple process variables.It is not easy to locate the root cause of the oscillations accurately.Moreover,there are few researches on the control strategies of the root cause of SOFC system oscillations.Aiming at the problem of variable oscillations during the experiment of SOFC system,a combination of data-driven causality and topology-based model is adopted in this thesis,which provides a complete procedure for diagnosing system oscillations.Facing the diagnosed root cause of the oscillations,an experimental system model is built,in which the oscillation situation is simulated,and an oscillation control strategy is developed in this thesis.Firstly,a 3k W SOFC power generation system is built in this thesis,and temperature-rising power generation experiment is started,including start-stop,standby and long-term discharge phases.It is found through experiment that many variables in SOFC system have oscillation problems.For the experimental subject,a SOFC system physical model is built through modeling and integration of various subsystems in SOFC system,and the model is verified by experimental data.Secondly,based on the numerous data obtained from the experiment,a method combining principal component analysis and oscillation significance index is chosen to select the characteristic variables in the system.Then the data-driven Granger causality analysis method is used to provide reliable diagnosis of the root cause of oscillations,and the topology model that takes the process connectivity and process knowledge into account further improves the accuracy of diagnosis result.The result shows that the combination of data and topology model can accurately locate the root cause of SOFC system oscillations,and provides a powerful guarantee for improving the accuracy of analyzing and diagnosing the root cause of system oscillations.Finally,based on the obtained oscillation root cause,the root cause of oscillations is simulated in the model,and a single-input controller and a dual-input fuzzy controller are further designed to control and eliminate the oscillation problem in system,thereby optimizing the problem of life being reduced and unstable power generation caused by oscillations in SOFC system.