Nonlinear MPC for the airflow in a PEM fuel cell using a Volterra series model

The particular industrial interest in fuel cells is based on the possibility to generate clean energy both for stationary and automotive applications. Performance and safety issues of fuel cells are closely related to the control strategy used for the fuel and oxidant supply. In PEM (polymer electrolyte membrane or proton exchange membrane) fuel cells the oxygen excess ratio expresses the proportion between oxygen reacting in the cells and oxygen entering the stack and represents a decisive variable for the mentioned issues. This work is focused on the design of a nonlinear model predictive control (NMPC) strategy manipulating the air flow rate in order to maintain the oxygen excess ratio in a desired value, both for safety and performance reasons. The designed NMPC, based on a second order Volterra series model, was implemented on a commercial fuel cell. The proposed NMPC strategy is validated in experiments and compared to a linear model predictive controller and to the original built-in controller.