Sensitivity and Bifurcation Analysis of a DAE Model for a Microbial Electrolysis Cell
Harry J. Dudley, Lu Lu, Zhiyong Jason Ren, and David M. Bortz

TL;DR
This paper develops a DAE model for microbial electrolysis cells, analyzing sensitivity and bifurcations to understand parameter impacts and stability regimes for optimizing hydrogen production.
Contribution
It introduces a novel DAE model for MECs and applies sensitivity and bifurcation analysis to identify key parameters and stability conditions for system optimization.
Findings
Growth parameters significantly influence peak current density.
Stable non-zero current equilibrium depends on dilution rate.
Multiple bifurcation regimes affect long-term current stability.
Abstract
Microbial electrolysis cells (MECs) are a promising new technology for producing hydrogen cheaply, efficiently, and sustainably. However, to scale up this technology, we need a better understanding of the processes in the devices. In this effort, we present a differential-algebraic equation (DAE) model of a microbial electrolysis cell with an algebraic constraint on current. We then perform sensitivity and bifurcation analysis for the DAE system. The model can be applied either to batch-cycle MECs or to continuous-flow MECs. We conduct differential-algebraic sensitivity analysis after fitting simulations to current density data for a batch-cycle MEC. The sensitivity analysis suggests which parameters have the greatest influence on the current density at particular times during the experiment. In particular, growth and consumption parameters for exoelectrogenic bacteria have a strong…
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Taxonomy
TopicsMicrobial Fuel Cells and Bioremediation · Advanced battery technologies research · Electrocatalysts for Energy Conversion
