LQR Optimal Control Strategy for Oxygen Excess Ratio in Proton Exchange Membrane Fuel Cells

Abstract:

In this paper， A sixth-order model of air supply system of a proton exchange membrane fuel cell （PEMFC） was established. PID control and linear quadratic regulator （LQR） control were combined with neural network feedforward control to form two composite control strategies respectively， and the response and stability of the oxygen excess ratio （OER） during variable load were compared under two composite control strategies. In the design of the LQR controller， the model was first linearized through a single equilibrium point to obtain the state feedback gain and the reduced-order state observer gain. Simulation results show that the composite control strategy combining neural network feedforward and LQR is significantly better than the other control strategies in the full range of operating conditions， subject to linearization of the single equilibrium point. Aiming at the situation that the control effect was degraded in the working condition far away from the equilibrium point， the method of multi-equilibrium point linearization was further adopted to optimize the design of the LQR controller to dynamically adjust the corresponding gain. The results show that the multi-equilibrium points LQR control method exhibits the best rapid response and stability in OER control.