Modelica based modelling and control design of counter-flow SOFC system considering temperature distribution
Lei Xia,
Jiafeng Wu,
Ali Khosravi and
Li Sun
Energy, 2025, vol. 331, issue C
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.
Keywords: MR-SOFC system; KF-MPC; Co-simulation; Load tracking; Temperature control (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544225026532
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:331:y:2025:i:c:s0360544225026532
DOI: 10.1016/j.energy.2025.137011
Access Statistics for this article
Energy is currently edited by Henrik Lund and Mark J. Kaiser
More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().