Parameter estimation of PEMFC based on Improved Fluid Search Optimization Algorithm - Fuzhen Qin; Peixue Liu; Haichun Niu; Haiyan Song; Nasser Yousefi (Energy Reports, 2020)
This paper presents a new optimal method for model estimation of the unknown parameters of circuit-based proton exchange membrane fuel cells (PEMFCs). The main idea is to minimize the sum of squared error (SSE) value between the actual data and the estimated results. The optimization process here is based on an Improved Fluid Search Optimization Algorithm (IFSO). For verification of the suggested method, it is applied to three practical case studies including Horizon H-12 stacks, NedStack PS6, and Ballard Mark V 5 kW under different operating conditions with temperature variations between 30 oC and 55o C and pressure variations between 1.0/1.0 Bar and 3.0/3.0 Bar. The results of these case studies are also compared with CGOA, MRFO, and basic FSO algorithm to show the proposed method's effectiveness. The results show that the minimum value of SSE among different algorithms is 0.7845, 2.15, and 0.084, respectively that are reached by the suggested IFSO algorithm.
Keywords: 330; Parameter estimation; Proton exchange membrane fuel; Improved fluid search optimization algorithm; The sum of square error