SOFC temperature evaluation based on an adaptive fuzzy controller

The operating temperature of a solid oxide fuel cell (SOFC) stack is a very important parameter to be controlled, which impacts the performance of the SOFC due to thermal cycling. In this paper, an adaptive fuzzy control method based on an affine nonlinear temperature model is developed to control the temperature of the SOFC within a specified range. Fuzzy logic systems are used to approximate nonlinear functions in the SOFC system and an adaptive technique is employed to construct the controller. Compared with the traditional fuzzy and proportion-integral-derivative (PID) control, the simulation results show that the designed adaptive fuzzy control method performed much better. So it is feasible to build an adaptive fuzzy controller for temperature control of the SOFC.

Numerical simulation of a direct internal reforming solid oxide fuel cell using computational fluid dynamics method

A detailed mathematical model of a direct internal reforming solid oxide fuel cell(DIR-SOFC) incorporating with simulation of chemical and physical processes in the fuel cell is presented. The model is developed based on the reforming and electrochemical reaction mechanisms,mass and energy conservation,and heat transfer. A computational fluid dynamics(CFD) method is used for solving the complicated multiple partial differential equations(PDEs) to obtain the numerical approximations. The resulting distributions of chemical species concentrations,temperature and current density in a cross-flow DIR-SOFC are given and analyzed in detail. Further,the influence between distributions of chemical species concentrations,temperature and current density during the simulation is illustrated and discussed. The heat and mass transfer,and the kinetics of reforming and electrochemical reactions have significant effects on the parameter distributions within the cell. The results show the particular characteristics of the DIR-SOFC among fuel cells,and can aid in stack design and control.

Predictive control of a direct internal reforming SOFC using a self recurrent wavelet network model

In this paper,an application of a nonlinear predictive controller based on a self recurrent wavelet network (SRWN) model for a direct internal reforming solid oxide fuel cell (DIR-SOFC) is presented. As operating temperature and fuel utilization are two important parameters,the SOFC is identified using an SRWN with inlet fuel flow rate,inlet air flow rate and current as inputs,and temperature and fuel utilization as outputs. To improve the operating performance of the DIR-SOFC and guarantee proper operating conditions,the nonlinear predictive control is implemented using the off-line trained and on-line modified SRWN model,to manipulate the inlet flow rates to keep the temperature and the fuel utilization at desired levels. Simulation results show satisfactory predictive accuracy of the SRWN model,and demonstrate the excellence of the SRWN-based predictive controller for the DIR-SOFC.