Abstract
Proton Exchange Membrane Fuel Cells (PEMFCs) are the main focus of their current development as power sources because they are capable of higher power density and faster start-up than other fuel cells. The humidification system and output performance of PEMFC stack are briefly analyzed. Predictive control of PEMFC based on Support Vector Regression Machine (SVRM) is presented and the SVRM is constructed. The processing plant is modelled on SVRM and the predictive control law is obtained by using Particle Swarm Optimization (PSO). The simulation and the results showed that the SVRM and the PSO receding optimization applied to the PEMFC predictive control yielded good performance.
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Project (No. 2003AA517020) supported by the Hi-Tech Research and Development Program (863) of China
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Ren, Y., Cao, Gy. & Zhu, Xj. Particle Swarm Optimization based predictive control of Proton Exchange Membrane Fuel Cell (PEMFC). J. Zhejiang Univ. - Sci. A 7, 458–462 (2006). https://doi.org/10.1631/jzus.2006.A0458
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DOI: https://doi.org/10.1631/jzus.2006.A0458