Robust control strategies for hybrid solid oxide fuel cell systems

Solid Oxide Fuel Cell (SOFC) systems are electrochemical energy conversion devices characterized by the use of solid oxide as the electrolyte. They operate at high temperatures (between 800± ¡ 1000±C). Mitigating fuel starvation and improving load-following capability of SOFCs are conflicting control objectives. In this thesis, this issue is addressed using a hybrid SOFC ultra-capacitor configuration. The fuel cell is controlled by incorporating a steady-state property of fuel utilization into an input-shaping framework. Two comprehensive control strategies are developed. The first is a Lyapunov-based nonlinear control and the second is a standard H-infinity robust control. Both strategies additionally control the state of charge (SOC) of the ultra-capacitor that provides transient power compensation. A hardware-in-the-loop test-stand is developed where the proposed control strategies are verified. An investigation to improve the hybrid fuel cell system by incorporating a lithium-ion battery as an additional power source is conducted. Combining both battery and ultra-capacitor with a fuel cell is potentially a winning combination especially for high power applications. A novel SOC estimation method for lithium-ion battery is investigated. Based on the combined ultra-capacitor battery hybrid system, a lyapunov-Based nonlinear control strategy is designed

Dynamic Behavior and Management Strategy of Hybrid Wind/Fuel Cell System

Abstract: hybrid generation system is considered as a solution for the uncontrolled energy production from such dispersed sources as wind generation. In this paper, modeling and control of wind/FC system is proposed. Dynamics models for the main system components, namely, wind energy conversion system (WECS), fuel cell, electrolyses, power electronic interfacing circuits, hydrogen storage tank and ultra-capacitor are developed. Also, a variable speed wind generation maximum power point tracking (MPPT) based on Adaptative Neuro-Fuzzy Inference system (ANFIS) is presented. Based on the dynamic component model, a simulation model for the proposed hybrid energy system has been developed using Matlab/Simulink and the power flows management strategy are proposed. The result shows that this system can tolerate the rapid changes in wind speed and/or power demand. This results shows also that, the overall power management strategy is effective and the power flows among the different energy sources and the load demand is balanced successfully