Operating States Modeling and Fault-tolerant Control of PEMFC Based on LSTM-MPC
Proton exchange membrane fuel cell(PEMFC)has multi-physics coupling characteristics,so PEMFC is prone to different faults and difficult to control.In order to control the fault quickly and effectively,a fault tolerant control scheme for PEMFC based on model predictive control(MPC)is proposed.First,the LSTM model prediction error is taken as the fitness function of genetic algorithm to obtain the optimal long short-term memory(LSTM)hyperparameter combination.Based on data drive,the LSTM prediction model of PEMFC system under four different operating states is established,which is used as the prediction model module.Moreover,the optimal controller based on neural network is established as the controller module,and the fault tolerant control scheme is developed,which takes the input gas pressure of anode and cathode of PEMFC system as the control quantity and the reactor voltage as the output quantity.Finally,the simulation verifies the LSTM prediction model and the fault tolerant control scheme,and the root mean square error(RMSE)index values of the LSTM prediction model in the training set and the test set are 0.0489 and 0.0558,respectively,showing a good fitting effect.Compared with the traditional PID fault-tolerant control scheme,the voltage recovery time of MPC is shortened by 50%or more under different fault states,and the maximum voltage drop is reduced by 22.2%under the hydrogen leakage fault state,which proves the effectiveness and correctness of the proposed control strategy.
proton exchange membrane fuel celldata-drivenneural networkmodel predictive controlfault-tolerant control
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