Feed-forward offset-free model predictive temperature control for proton exchange membrane fuel cell: An experimental study

Safe and economic operation of an open-cathode proton exchange membrane fuel cell (PEMFC) requires an efficient thermal management strategy. The stack temperature regulation in PEMFC is, however, challenging due to often stringent set-point tracking tasks, frequent load fluctuations, constrained manipulated variables, and various modeling uncertainties and nonlinearities. To this end, a feed-forward offset-free model predictive control (MPC) approach, aiming at uncertainties resolving and disturbance mitigation, is developed to simultaneously address the above difficulties. In the proposed framework, the information about the measured power load fluctuations is used in the optimization algorithm as feed-forward information to eventually mitigate the influence of load fluctuations on the controlled output and increases the overall control quality. Additionally, the unmodeled dynamics and the other unmeasurable disturbances/uncertainties are collectively considered as an extended state of the system (to achieve zero static errors) and the on-line reconstructed aggregated disturbances is continuously sent to the MPC algorithm to increase its optimization performance and to achieve offset-free control objectives. The obtained results are quantitatively compared with conventional control strategies for PEMFCs, including a model-based PI controller, its modification utilizing disturbance feed-forward, and a standard offset-free MPC (i.e. without feed-forward). Both the simulations, realized in MATLAB/Simulink, and hardware experiments, conducted on a 500 W PEMFC testbed, show excellence of the proposed feed-forward offset-free MPC consisting in faster temperature tracking and higher robustness. The obtained satisfactory results show the introduced control solution to be a promising prospect and help accelerating further applications of PEMFCs.