4.7 Article

Oxygen excess ratio control for proton exchange membrane fuel cell using model reference adaptive control

Journal

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
Volume 44, Issue 33, Pages 18425-18437

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ijhydene.2019.05.041

Keywords

Model reference adaptive control; Proton exchange membrane fuel cell; Oxygen excess ratio; Adaptive mechanism; Adaptive control law

Funding

  1. Technology Innovation Program - Ministry of Trade, Industry & Energy (MOTIE, Republic of Korea) [10084611]
  2. National Research Foundation of Korea (NRF) - Ministry of Science, ICT and Future Planning [2017R1A2B4006528]
  3. Korea Evaluation Institute of Industrial Technology (KEIT) [10084611] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
  4. National Research Foundation of Korea [2017R1A2B4006528] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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Optimized robust oxygen excess ratio (OER) control for proton exchange membrane fuel cells (PEMFCs) is now a critical issue for improving their economic efficiency and performance. In general, it is very difficult to control the OER due to modeling errors, parameter uncertainties, and disturbances. To address these issues, we propose a control system based on model reference adaptive control (MRAC) various difficulties inherent air supply systems. We utilize an adaptive law to address uncertainties implementation of the MRAC and nominal feedback controllers on a nonlinear model of fuel cell system is presented for illustration of the proposed system's robustness with various operating conditions. In addition, the control performance of MRAC is compared with nominal feedback control. The results show that the presented MRAC strategy performs better than the nominal feedback control method with less wear and less control effort on the compressor. The proposed MRAC algorithm can increase the compressor efficiency by using the adaptive law even with uncertainties. (C) 2019 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

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