Polymer electrolyte fuel cells (PEFCs) have attracted considerable interest within the research community due to the increasing demands for renewable energy. Within the PEFCs’ many components, a cathode electrode plays a primary function in the operation of the cell. Here, a computational-intelligence-aided design and engineering (CIAD/CIAE) framework with potential cross-disciplinary applications is proposed to minimize the over-potential difference η and improve the overall efficiency of PEFCs. A newly developed swarm dolphin algorithm is embedded in a computational-intelligence-integrated solver to optimize a triple-layer cathode electrode model. The simulation results demonstrate the potential application of the proposed CIAD/CIAE framework in the design automation and optimization of PEFCs. 
Multi-objective optimization on multi-layer configuration of cathode electrode for polymer electrolyte fuel cells via computational-intelligence-aided design and engineering framework