earticle

영어

Microbial fuel cells (MFCs) are bioelectrochemical devices which degrade organic substrate with help of consortia of micro-organisms as catalyst for electrogenesis in their anode; to produce electrical current. MFC power output is a function of many operating factors such as pH, temperature, loading rate, flow rate, and electrical load, which would define its state. However, the work presented here seeks to identify dynamic cause and effect relationships between key parameters and piecewise linearise the MFC process. A sandwich-type MFC was subjected to a varying electrical load of various Pseudo-Random and step inputs, while observing the MFC voltage. Nonlinear behaviour was inferred from assumed piecewise linearised first order dynamic responses, at different operating points. The time constants increased from 0.5 s with PRBS loading of 100 Ω – 150 Ω, to 6.2 s at 950 Ω – 1 kΩ; although steady state gain varied little, (0.12 mV Ω-1 to 0.20 mV Ω-1). This suggests that the MFC’s non-linear behaviour dependent on operating conditions may be adequately represented by a series of linear models. System Identification suggested that linear 4rd order ARX models had the best fit. However, reasonable prediction was observed using piecewise linearised first order models. The models could be used to design and optimize controllers to regulate power and/or voltage generation.