Optimal Parameter Estimation Methodology of Solid Oxide Fuel Cell Using Modern Optimization

An optimal parameter estimation methodology of solid oxide fuel cell (SOFC) using modern optimization is proposed in this paper. equilibrium optimizer (EO) has been used to identify the unidentified parameters SOFC equivalent circuit with assistance experimental results. This presented via formulating modeling process as an problem considering sum mean squared error (SMSE) between observed and computed voltages target. Two modes SOFC-based model are investigated under variable operating conditions, namely, steady-state dynamic-state based models. The EO results compared those obtained Archimedes algorithm (AOA), Heap-based (HBO), Seagull Optimization Algorithm (SOA), Student Psychology Based (SPBO), Marine predator (MPA), Manta ray foraging (MRFO), comprehensive learning dynamic multi-swarm marine predators algorithm. minimum fitness function at value 1.5527 × 10−6 1173 K. In model, SMSE 1.0406. confirmed reliability superiority constructing a reliable SOFC.