Design of model-based control strategies for a novel MISO PEM fuel cell control structure

Voltage control is critical for the performance of proton exchange membrane fuel cells. However, accurately controlling voltage is challenging, specifically during the current variation. The present study proposes a novel multiple-input single-output (MISO) control structure for a proton exchange membrane fuel cell system to improve performance. Also, this study focuses on airflow optimization and hydrogen consumption optimization, as the literature focuses more on airflow optimization for compressor or pump performance. Firstly, using a genetic algorithm optimization technique, the fractional order model is realized from the existing integer order fuel cell model. Then, the proposed control structure aims to control the output cell voltage by regulating the air and hydrogen inlet rates by designing various model-based controllers for integer and fractional order models. The control performance is evaluated for set point tracking, disturbance rejection, inverse response rejection and time delay compensation. The simulation results show that the fractional order system is observed to give better results than the integer order system, with model predictive controller showing the best results for controlling the stack voltage.