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Modelica based modelling and control design of counter-flow SOFC system considering temperature distribution

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  • Xia, Lei
  • Wu, Jiafeng
  • Khosravi, Ali
  • Sun, Li

Abstract

In this study, a counter-flow methane reforming solid oxide fuel cell (MR-SOFC) system is proposed. Based on the response data of the system, a nonlinear least squares (NLS) identification method is used to identify the state space model, and a Kalman filter-based model prediction control (KF-MPC) is developed in SIMULINK. Finally, the co-simulation framework of Modelica/SIMULINK is developed to investigate the control performance of KF-MPC. The results show that the tracking accuracy and speed for the KF-MPC system are superior to those of proportional-integral-derivative (PID) in large-scale load changes and load fluctuations. The shortest settling time (tst) for net output power (Pnet) is 15s, which is only 24.19% of that of the PID in large-scale load changes. During load fluctuations, the maximum value of the root mean square error (RMSE) for Pnet in KF-MPC is 0.0372 kW, lower than that of PID (0.0948 kW) and only 39.23% of it. The tst in the KF-MPC system is 7s, much lower than the 285s in PID, at the step change of SOFC cathode inlet temperature (Tin). A large overshoot of Tin occurs in the PID system, and its RMSE (2.23 K) is higher than that (0.42 K) of the KF-MPC system. The maximum temperature gradient (max|ΔTPEN|) of the SOFC in the KF-MPC system is 19.94 K/cm, smaller than that of the PID. The temperature change rate of each node of the SOFC in the KF-MPC system is significantly smoother and the system operates more reliably during the control process.

Suggested Citation

  • Xia, Lei & Wu, Jiafeng & Khosravi, Ali & Sun, Li, 2025. "Modelica based modelling and control design of counter-flow SOFC system considering temperature distribution," Energy, Elsevier, vol. 331(C).
    • Handle: RePEc:eee:energy:v:331:y:2025:i:c:s0360544225026532
    DOI: 10.1016/j.energy.2025.137011
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