During the actual operation of the solid oxide fuel cell (SOFC), degradation is one of the most difficult technical problems to overcome. Predicting the degradation trend and estimating the remaining useful life (RUL) can effectively diagnose the potential failure and prolong the useful life of the fuel cell. To study the degradation trend of the SOFC under constant load conditions, a SOFC degradation model based on the ohmic area specific resistance (ASR) is presented first in this paper. Based on this model, a particle filter (PF) algorithm is proposed to predict the long-term degradation trend of the SOFC. The prediction performance of the PF is compared with that of the Kalman filter, which shows that the proposed algorithm is equipped with better accuracy and superiority. Furthermore, the RUL of the SOFC is estimated by using the obtained degradation prediction data. The results show that the model-based RUL estimation method has high accuracy, while the excellence of the PF algorithm for degradation trend prediction and RUL estimation is proven.
Nowadays, the temperature gradient is considered as one of the most important parameters which impact the performance of the solid oxide fuel cell (SOFC). In this paper, a control strategy based on an input−output feedback linearization technology is derived for controlling the maximum temperature gradient within the anode fuel flow channel at the desired value. For the controller design, the temperature dynamic model is proposed and simplified to a controloriented multi-input and multioutput nonlinear dynamic model. Then, this paper presents an input−output feedback linearization controller to realize the control objective by adjusting the cathode input air flow. Finally, the simulation results are given to demonstrate the accuracy of the proposed model in reflecting the temperature dynamic characteristics. Moreover, the compound controller is added for simulation as a comparison, which shows that the proposed controller is equipped with better effectiveness and efficiency in the presence of external disturbances.
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