Abstract-In this paper, the design of a nonlinear observerbased fault diagnosis approach for polymer electrolyte membrane (PEM) fuel cell air feed systems is presented, taking into account a fault scenario of sudden air leak in the air supply manifold. Based on a simplified nonlinear model proposed in the literature, a modified super-twisting (ST) sliding mode algorithm is employed to the observer design. The proposed ST observer can estimate not only the system states, but also the fault signal. Then, the residual signal is computed on-line from comparisons between the oxygen excess ratio obtained from the system model and the observer system, respectively. Equivalent output error injection using the residual signal is able to reconstruct the fault signal, which is critical in both fuel cell control design and fault detection. Finally, the proposed observer-based fault diagnosis approach is implemented on the Matlab/Simulink environment in order to verify its effectiveness and robustness in the presence of load variation.
If citing, it is advised that you check and use the publisher's definitive version for pagination, volume/issue, and date of publication details. And where the final published version is provided on the Research Portal, if citing you are again advised to check the publisher's website for any subsequent corrections.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.