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Energy Systems Research

Energy Systems Modeling

  1. Development of detailed mathematical models of reformer based SOFC (Solid Oxide Fuel Cell) systems.
  2. Development of a hierarchical arrangement of model libraries that facilitates simulation with different fuels (methane, JP8, etc.), reformers (Steam Reformer, Partial Oxidation Reformer, Auto-thermal Reformer) and stack technologies (Planar, Tubular SOFC).
  3. Development of storage element models (Ultra-capacitor, Li-Ion, Lead-acid) and renewable energy system (wind-turbine system) models.

Real-time Simulation and Energy System Emulation

  1. Enables control verification
  2. Enables hardware-in-the-loop system development

Fuel cell characterization and optimization

  1. Transient characteristics are critical in control design for fuel cell based power plants.
  2. Leads to prediction of transient behaviors with varied time scales and extraction of steady state properties.
  3. Systems analysis also enables fuel optimization.
  4. Model independent characterization and derivation of invariant properties of a class of reformer based SOFC systems.

Control of Hybrid Fuel Cell Systems

  1. Hybridization of SOFC with ultra-capacitors and Li-Ion batteries are explored.
  2. Optimal load-sharing between fuel cell and battery/super-capacitor is necessary to prolong stack life and improve transient load-following capability.
  3. Control designs that address stack-life, SOC control for energy storage devices, etc. simultaneously, are pursued (e.g. robust nonlinear control, H-infinity control, etc.)

Plasma-based fuel reformers

  1. Plasma based reforming techniques has the potential for providing better energy efficiency of hydrogen production from hydrocarbons.
  2. Modeling and system dynamics of plasma based reformers are explored.

Observer designs for SOFC systems

  1. Accurate system information requires species concentration measurement in various control volumes throughout the fuel cell system.
  2. Observer designs reduce the number of concentration sensors required for control.
  3. The designs exploit steady-state properties of the system and/or employ adaptive parameter estimation techniques.