Dynamics and control of a turbocharged solid oxide fuel cell system

The purpose of this paper regards the design and testing of control systems for a 30-kW turbocharged solid oxide fuel cell system fuelled with biogas. The adoption of a turbocharger, instead of a micro gas turbine, for the fuel cell stack pressurisation, is an innovative solution that is expected to decrease the capital cost of such systems and to facilitate their penetration into the energy market. However, not being connected to an electric generator, the turbocharger rotational speed, and thus the air mass flow, cannot be directly controlled as in microturbines. The control of turbocharged solid oxide fuel cell systems is a novel topic, characterised by many technical challenges that have not been addressed before. To regulate the stack temperature, a cold bypass valve is included, connecting the compressor outlet to the turbine inlet. A dynamic model of this system was developed in Matlab-Simulink (R) to analyse the response of the turbocharged solid oxide fuel cell system to a cold bypass valve opening step change. System information obtained from this analysis was used to design and tune four controllers: a conventional proportional integral controller and three different cascade controllers. The controller performance was evaluated under two different scenarios, considering quite aggressive power ramps. The best results were obtained with a cascade controller, where the feedback loop was complemented by a feed-forward contribution based on power demand. This analysis demonstrated that such a control system effectively tracks the fuel cell maximum temperature target, complying with all the system operative constraints.

Automated summary

The research aims to design and test a control system for a 30-kW turbocharged solid oxide fuel cell system fueled with biogas. The innovative use of a turbocharger for pressurizing the fuel cell stack is expected to reduce capital costs and increase market penetration. Results show that a cascade controller performs the best, effectively tracking the fuel cell's maximum temperature target and meeting all operational constraints.