Abstract
In this paper, the design of a nonlinear observer-based 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 online 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.
| Original language | English |
|---|---|
| Article number | 7420651 |
| Pages (from-to) | 3261-3270 |
| Number of pages | 10 |
| Journal | IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS |
| Volume | 63 |
| Issue number | 5 |
| Early online date | 26 Feb 2016 |
| DOIs | |
| Publication status | Published - May 2016 |
Keywords
- Fault diagnosis
- polymer electrolyte membrane (PEM) fuel cells
- super-twisting (ST) algorithm
Access to Document
- Robust Model-Based Fault Diagnosis_LIU_Accepted 4Feb2016_GREEN AAM
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