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Design and implementation of model predictive control for an open-cathode fuel cell thermal management system

Author

Listed:
  • Zhang, Bo
  • Lin, Fei
  • Zhang, Caizhi
  • Liao, Ruiyue
  • Wang, Ya-Xiong

Abstract

The aim of this study is to design a thermal management system to address the temperature regulation and fluctuation of an open-cathode proton exchange membrane (PEM) fuel cell. A model predictive control (MPC) approach is newly proposed to command of blowers in the fuel cell. First, a thermal management-oriented model of the fuel cell is set up, and linearized by using Taylor formula. Then, the closed-loop feedback MPC according to the linearized state-space model is developed. An experimental test rig via LabVIEW-based thermal control system prototype is configured. Finally, different load current tests were applied to verify the effectiveness, and the performance of the MPC controller was compared with a traditional PI controller. The results of this study demonstrate that the proposed MPC can effectively manipulate the stack temperature to track the reference trajectory under the constant current as well as dynamic load schedules. In particular, in a combined driving cycle equivalent test condition, the fuel cell temperature reached to the target after a settling time of 146.6 s, and temperature fluctuations were less than ±0.5 °C with the MAE value of 0.223 and the RMSE value of 0.346.

Suggested Citation

  • Zhang, Bo & Lin, Fei & Zhang, Caizhi & Liao, Ruiyue & Wang, Ya-Xiong, 2020. "Design and implementation of model predictive control for an open-cathode fuel cell thermal management system," Renewable Energy, Elsevier, vol. 154(C), pages 1014-1024.
    • Handle: RePEc:eee:renene:v:154:y:2020:i:c:p:1014-1024
    DOI: 10.1016/j.renene.2020.03.073
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    References listed on IDEAS

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