Adaptive observer based approach for the fault diagnosis in solid oxide fuel cells

Monitoring and fault diagnosis can play a major role in improving the reliability of Solid Oxide Fuel Cell (SOFC) systems. Due to complex interactions between the variables, quantitative model based methods are suitable for SOFC fault diagnosis. In this work, a fault diagnosis strategy based on a non-linear observer based approach is proposed for the SOFC. Two nonlinear adaptive observers are designed based on the concepts of input-to-state stability of cascaded systems, each sensitive to different faults affecting the SOFC. Simultaneous application of these two observers allows the unique identification and diagnosis of all the common faults in the SOFC. This unique approach of multiple nonlinear adaptive observers for SOFC fault diagnosis can improve fault resolution and has applicability over wide operating ranges.