PERFORMANCE ANALYSIS AND CONTROL OF SOLID OXIDE FUEL CELLS WITH DIRECT INTERNAL REFORMING

Abstract

This research focuses on the performance analysis and control of a solid oxide fuel cell (SOFC) with direct internal reforming using methane as fuel. Firstly, the steady state analysis is performed to design the optimal operational condition for this system. The direct internal reforming of methane in SOFC can utilize the heat from the exothermic electrochemical reaction to produce hydrogen-rich gas, leading to an increasing system efficiency. However, the coupling of the endothermic reforming and electrochemical reactions results in a complicated dynamic response. Therefore, the effect of input variables on the cell temperature and cell voltage is analyzed to investigate the dynamic behavior that is important for design a controller. It is found that the cell operating temperature and cell voltage are dependent on the fuel and air inlet temperature as well as the current density. Next, to achieve the efficient control system, the control structure design of the SOFC is considered to identify good controlled variables and manipulated variables. The concept of a controllability analysis is applied to the control system design of the SOFC for the selection of input-output pairings by considering the relative gain array (RGA). The result shows that the inlet molar flow rates of air and fuel are manipulated variables to control the cell temperature and the content of fuel, respectively. Finally, the conventional and advanced control techniques are designed and implemented to control the cell temperature, the content of methane and the cell voltage. In this research, the model predictive control (MPC) that is a model-based control strategy is proposed for SOFC control. In general, MPC requires the accurate and reliable model of the process to be controlled. However, the SOFC model is complicated and involves uncertain parameters. Therefore, an off-line robust MPC algorithm is developed and employed for controlling the SOFC. The robust MPC algorithm based on linear time-varying (LTV) and linear parameter varying (LPV) systems is also studied. The simulation results show that under the model uncertainty, the proposed robust MPC can control the SOFC and guarantee the stability of the SOFC. The robust MPC algorithm using the LPV model of the SOFC can achieve a better control performance because the model parameters are on-line updated and used in the control calculation.