Finding best operational conditions of PEM fuel cell using adaptive neuro-fuzzy inference system and metaheuristics

The optimum output power of the proton exchange membrane fuel cell (PEMFC) is dependent on operational conditions such as pressure, oxidant flow rate, and rate. Therefore, aim this paper to enhance performance PEMFC by identifying optimal operating parameters PEMFC. proposed strategy includes both modelling optimization stages. An adaptive network-based fuzzy inference system (ANFIS) utilized in creating model based experimental datasets. Whereas, grey wolf optimizer (GWO) used identify best values rate corresponding maximum obtained results demonstrated superiority integration between ANIFS GWO. Regarding accuracy, RMSE are 0.017 well 0.0262 respectively for treating testing phases. coefficient determination 0.9921 0.9622 coupled with 1.0 bar, 0.8 117.03 mL/min, 150.0 mL/min Thanks ANFIS-based GWO, has been increased from 0.587 W using work 0.92 W.