Online gas composition estimation in solid oxide fuel cell systems with anode off-gas recycle configuration

Degradation and poisoning of solid oxide fuel cell (SOFC) stacks are continuously shortening the lifespan of SOFC systems. Poisoning mechanisms, such as carbon deposition, form a coating layer, hence rapidly decreasing the efficiency of the fuel cells. Gas composition of inlet gases is known to have great impact on the rate of coke formation. Therefore, monitoring of these variables can be of great benefit for overall management of SOFCs. Although measuring the gas composition of the gas stream is feasible, it is too costly for commercial applications. This paper proposes three distinct approaches for the design of gas composition estimators of an SOFC system in anode off-gas recycle configuration which are (i.) accurate, and (ii.) easy to implement on a programmable logic controller. Firstly, a classical approach is briefly revisited and problems related to implementation complexity are discussed. Secondly, the model is simplified and adapted for easy implementation. Further, an alternative data-driven approach for gas composition estimation is developed. Finally, a hybrid estimator employing experimental data and 1st-principles is proposed. Despite the structural simplicity of the estimators, the experimental validation shows a high precision for all of the approaches. Experimental validation is performed on a 10 kW SOFC system

Soft Sensor Design for Estimation of SOFC Stack Temperatures and Oxygen-to-Carbon Ratio

The life span of a solid oxide fuel cell (SOFC) stack depends on several factors, such as internal stack temperature and temperature gradients as well as the fuel gas oxygen-to-carbon (O/C) ratio. An excessive stack temperature generally accelerates the degradation, while large temperature gradients across the stack cause thermal stress, which leads to delamination. Too low O/C ratio inflicts carbon deposition, which quickly leads to stack breakage. Therefore, monitoring of these variables is of vital importance. Although direct sensing of temperatures within the stack as well as fuel gas composition in fuel stream is feasible, it is not desirable due to increased equipment cost. In this paper a data-driven design of soft sensors for minimal and maximal stack temperatures as well as the O/C ratio is presented. Dynamic and static models for stack temperature are identified from data and their performance is compared. The dynamic model is derived by means of the subspace identification, which results in a causal state-space model. The non-causal static model assumes that a combination of process variables at the stack inlet and outlet describe its internal condition. The estimator of O/C ratio is based on static relationships. The soft sensors are designed in such a way that adding extra inputs to the model yields no further increase in accuracy of the estimates. The empirical data required for modelling were obtained from a SOFC power generating unit. The results show that the reconstruction of all the relevant variables can be accomplished by simple linear regression models

Feedforward-Feedback Control of a SOFC Power System: A Simulation Study

In this paper a feedforward-feedback control design for solid oxide fuel cell (SOFC) power systems is proposed. The feedforward part of the controller reacts to the electrical current demand as well as the stoichometry of electro-oxidation and reforming processes. Feedback part performs corrections of the controlled system output by additional manipulation of system inputs. Based on relative gain analysis (RGA), it is found that two individual PI control loops turn out suitable enough to control the system. Parameters of the PI controllers are tuned on the basis of open-loop step response experiments by applying the Magnitude Optimum Multiple Integration method (MOMI). The proposed feedforward-feedback control is verified on the SOFC stack model over a one-day operation cycle using the standard load profile of residential houses. The main advantage of the proposed controller is its simple structure and easy tuning, which makes it feasible for practical implementation