The invention relates to the technical field of
solid fuel cells, and discloses a porous gradient
anode supported
solid fuel
cell impedance optimization method which is applied to a
system comprising a plurality of porous gradient
anode impedance sensors and an optimization controller. The method comprises the steps that a sensor collects
voltage and current data to generate an impedance state
data set; the optimization controller constructs a regional impedance state matrix, extracts features through
processing, performs
impedance distribution prediction in combination with a
potential gradient and the like, outputs spatial and temporal distribution features through an impedance optimization model, and updates a
data set; and dynamically optimizing regional
electrode parameters according to the distribution characteristics, including
voltage adjustment, current aggregation, resistance distribution and other operations. According to the method, through multi-sensor distributed acquisition, multi-dimensional feature analysis and dynamic modeling, accurate prediction and parameter dynamic regulation and control of
electrode impedance spatial and temporal distribution are realized, the performance and stability of the
solid fuel
cell are improved, and the method is suitable for the field of
solid fuel cell management.