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Experimental analysis of dynamic characteristics on the PEM fuel cell stack by using Taguchi approach with neural networks
Authors:Wei-Lung Yu  Sheng-Ju Wu  Sheau-Wen Shiah
Affiliation:1. Department of Vehicle Engineering, Army Academy, No. 113, Sec.4, Chun-San E. Rd., Chun-Li 320, Taiwan, ROC;2. Department of Power Vehicle and Systems Engineering, Chung Cheng Institute of Technology, National Defense University, No. 190, Sanyuan 1st St., Tashi, Taoyuan 335, Taiwan, ROC
Abstract:This study determines the optimum operating parameters for a proton exchange membrane fuel cell (PEMFC) stack to obtain small variation and maximum electric power output using a robust parameter design (RPD). The operating parameters examined experimentally are operating temperatures, operating pressures, anode/cathode humidification temperatures, and reactant flow rates. First, the dynamic Taguchi method is used to obtain the maximum and stable power density against the different current densities, which are regarded as the systemic inputs considered a signal factor. The relationship between control factors and responses in the PEMFC stack is determined using a neural network. The discrete parameter levels in the dynamic Taguchi method can be divided into desired levels to acquire real optimum operating parameters. Based on these investigations, the PEMFC stack is operated at the current densities of 0.4–0.8 A/cm2. Since the voltage shift is quite small (roughly 0.73–0.83 V for each single cell), the efficiency would be higher. In the range of operation, the operating pressure, the cathode humidification temperature and the interactions between operating temperature and operating pressure significantly impact PEMFC stack performance. As the operating pressure increasing, the increments of the electric power decrease, and power stability is enhanced because the variation in responses is reduced.
Keywords:Proton exchange membrane fuel cell stack  Robust parameter design  Dynamic characteristics  Artificial neural network
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