Optimal Control Of Solid Oxide Fuel Cell System Considering Performance Degradation

Solid Oxide Fuel Cell is a high-temperature fuel cell.It is a new type of power generation device.It has many advantages,such as high efficiency,zero emission and low noise,which have attracted wide attention of researchers.At present,the research on SOFC system mainly focuses on how to ensure the stable operation of the system and how to achieve the optimal system efficiency and cost while ensuring the stable operation of the system.However,since a solid oxide fuel cell operates at a high temperature,its constituent components may deteriorate in performance due to chemical reactions or physical interactions between each other.What is more,the fuel cell performance may be degraded due to changes in the material or structure of the component itself,even failed.Therefore,the influence of degradation factors on SOFC system is considered in this paper,and the optimal control of SOFC system based on degradation is studied.The main research contents are as follows:(1)Building the degradation model of SOFC system.Firstly,based on the knowledge of electrochemistry and thermodynamics,the core components(stack)and peripheral equipment(air compressor,heat exchanger,bypass valve,combustion chamber,mixer)of SOFC system are studied by modularization method under the condition of satisfying the conservation of mass and energy.Then,considering the degradation of fuel cell performance caused by the change of anode nickel material in the stack,the model of nickel coarsening and nickel oxidation is built,and the sub-models are connected according to the corresponding technological process to form a complete SOFC power generation system.Finally,on the platform of MATLAB,the degradation model of SOFC system is simulated and verified by using the simulation tool SIMULINK.The verification results show that the degradation model built in this paper can accurately reflect the actual output characteristics of the system.(2)A dynamic particle swarm optimization based on control vector parameterization is proposed for SOFC systems considering performance degradation.The optimization algorithm first uses the control vector parameterization method to transform an infinite dimensional dynamic optimization problem into a finite dimensional static optimization problem.Then,the particle swarm optimization algorithm is used to minimize the decay rate of the SOFC system,and the effectiveness of the optimization algorithm is verified by comparing the optimal decay rate results at different times.Finally,based on the optimal operation trajectory(fuel utilization rate,air excess ratio and stack temperature)obtained by the dynamic optimization,we use the iterative learning controller to construct the PD-type learning law to achieve tracking control.The simulation results show that with the change of time,the control strategy can ensure the system has good stability and fast convergence speed while ensuring the minimum system degradation rate.(3)As the SOFC system is in a recession process,power generation efficiency will also decrease.Therefore,this paper proposes a multi-objective optimization and control strategy that maximizes the system's power generation efficiency while minimizing system degradation rates.Firstly,the dynamic operating point of the SOFC system under performance degradation is obtained by the dynamic NSGA-II optimization algorithm and the TOPSIS method.Then the optimal operating point is set as the target reference value of the controller to optimize the SOFC system degradation rate and efficiency.Control allows the SOFC system to operate stably and efficiently with optimal rate and efficiency at each moment.