Model Predictive Control for Regulating Fuel Cell Stack Temperature and Air Flow Rate

Abstract

Stack temperature and airflow rate are vital control problems for Proton Exchange Membrane fuel cell (PEMFC). Two separate Model Predictive Controllers (MPC) have been employed to regulate these problems. The controllers utilized Laguerre and exponential weight functions to reduce its numerical instability and computational time. The temperature MPC considered delayed and constrained coolant pump voltage as manipulated input and stack temperature as the desired output. While airflow MPC manipulated compressor motor voltage to maintain the desired level of oxygen excess ratio subjected to starvation, surge, and choke constraints. Results showed that both controllers worked well together. The desired temperature and oxygen excess ratio were maintained subjected to all the constraints, even with the presence of external disturbances. This study highlights that MPC manages to handle both control problems without any conflict. Yet, it also proves that MPC can handle a large time delay process.