Multilinear-Model Predictive Control of a Tubular Solid Oxide Fuel Cell System

Abstract

As solid oxide fuel cells (SOFCs) are highly nonlinear systems, a single linear controller cannot perform satisfactorily over a wide range of operating conditions of the processes. This work studies multilinear-model predictive control of a tubular SOFC. The objective is to control the fuel cell outlet voltage over a wide range of operating conditions by manipulating inlet fuel pressure (flow rate). A first-principles model of an ammonia fed-tubular solid oxide fuel cell is used for the controller design. The model accounts for diffusion, inherent impedance, transport (momentum, heat and mass transfer), electrochemical reactions, activation and concentration polarizations, and the ammonia decomposition reaction. The servo and regulatory performances of the multimodel predictive controller (MMPC) are compared with those of a single-model predictive controller (SMPC) and a proportional-integral (PI) controller. For small load changes, the MMPC, SMPC, and PI controller all provide zero offset, and the MMPC yields the best closed-loop performance. However, for large load changes, the SMPC and PI controller fail to provide zero offset; under these two controllers the closed-loop system with the large load changes is unstable.