Dynamic modeling, model-based control, and optimization of solid oxide fuel cells

Simple item page
dc.contributor.advisorEdgar, Thomas F.en
dc.contributor.committeeMemberBonnecaze, Rogeren
dc.contributor.committeeMemberChen, Dongmeien
dc.contributor.committeeMemberMeyers, Jeremyen
dc.contributor.committeeMemberRochelle, Garyen
dc.creatorSpivey, Benjamin Jamesen
dc.date.accessioned2011-10-12T16:36:13Zen
dc.date.accessioned2017-05-11T22:23:31Z
dc.date.available2011-10-12T16:36:13Zen
dc.date.available2017-05-11T22:23:31Z
dc.date.issued2011-08en
dc.date.submittedAugust 2011en
dc.date.updated2011-10-12T16:36:37Zen
dc.descriptiontexten
dc.description.abstractSolid oxide fuel cells are a promising option for distributed stationary power generation that offers efficiencies ranging from 50% in stand-alone applications to greater than 80% in cogeneration. To advance SOFC technology for widespread market penetration, the SOFC should demonstrate improved cell lifetime and load-following capability. This work seeks to improve lifetime through dynamic analysis of critical lifetime variables and advanced control algorithms that permit load-following while remaining in a safe operating zone based on stress analysis. Control algorithms typically have addressed SOFC lifetime operability objectives using unconstrained, single-input-single-output control algorithms that minimize thermal transients. Existing SOFC controls research has not considered maximum radial thermal gradients or limits on absolute temperatures in the SOFC. In particular, as stress analysis demonstrates, the minimum cell temperature is the primary thermal stress driver in tubular SOFCs. This dissertation presents a dynamic, quasi-two-dimensional model for a high-temperature tubular SOFC combined with ejector and prereformer models. The model captures dynamics of critical thermal stress drivers and is used as the physical plant for closed-loop control simulations. A constrained, MIMO model predictive control algorithm is developed and applied to control the SOFC. Closed-loop control simulation results demonstrate effective load-following, constraint satisfaction for critical lifetime variables, and disturbance rejection. Nonlinear programming is applied to find the optimal SOFC size and steady-state operating conditions to minimize total system costs.en
dc.description.departmentChemical Engineeringen
dc.format.mimetypeapplication/pdfen
dc.identifier.slug2152/ETD-UT-2011-08-4325en
dc.identifier.urihttp://hdl.handle.net/2152/ETD-UT-2011-08-4325en
dc.language.isoengen
dc.subjectModel predictive controlen
dc.subjectLinear system identificationen
dc.subjectFirst principles modelingen
dc.subjectSolid oxide fuel cellsen
dc.subjectEconomic optimizationen
dc.subjectNonlinear programmingen
dc.titleDynamic modeling, model-based control, and optimization of solid oxide fuel cellsen
dc.type.genrethesisen

Files

Collections

University of Texas at Austin