Robust Model Predictive Control Strategy for LTV and LPV Systems of the Internal Reforming Solid Oxide Fuel Cell

Abstract

Abstract Solid oxide fuel cell (SOFC) is an electrochemical device operating at a high temperature, converting the chemical energy of a fuel directly to electrical energy. Moreover, it can directly convert hydrocarbon fuels to a hydrogen-rich gas via internal reforming inside the fuel cell stack itself. However, the endothermic cooling effect resulting from the reforming reaction at the anode side causes the temperature gradient and thermal stress within the fuel cell stack. This requires an efficient control design for assuring a stability of the system. In this study, a robust linear model predictive control (MPC) based on uncertain polytopic approach is synthesized for controlling the SOFC. Different designs of the robust MPC using linear time-varying (LTV) and linear parameter varying (LPV) models are studied. The state feedback control laws are derived by minimizing an upper bound on the worst-case performance cost and are implemented to the cell voltage and temperature controls of the direct internal reforming SOFC. The simulation results show that under model uncertainties, the proposed robust MPC can control the SOFC when disturbances in the fuel feed and air temperature are introduced and guarantee the stability of the SOFC. The performance of the MPC using different linear models is compared and discussed.