A new technique for optimal estimation of the circuit-based PEMFCs using developed Sunflower Optimization Algorithm

This paper proposes a new methodology for the optimal selection of the parameters for proton exchange membrane fuel cell (PEMFC) models. The proposed method is to optimal parameter selection of the circuit-based model of the PEMFC model to minimize the sum of squared error (SSE) value between the estimated and the actual output voltage of the PEMFC stack. For minimizing the SSE, a newly developed model of the Sunflower Optimization Algorithm (DSFO) is proposed. Performance analysis is performed based on two practical models including NedSstack PS6 PEMFC and Horizon 500-W PEMFCs from the literature and the results have been compared with the empirical data and also some state of art methods including Seagull Optimization Algorithm (SOA), Multi-verse optimizer (MVO), and Shuffled Frog-Leaping Algorithm (SFLA). Final results indicate 2.18 and 0.014 SSE value for NedSstack PS6 PEMFC and Horizon 500-W open cathode PEMFC, respectively which are the minimum values compared with the other compared methods. (C) 2020 The Authors. Published by Elsevier Ltd.