Li Guanru, Fu Hao, Madonski Rafal, Czeczot Jacek, Nowak Pawel, Lakomy Krzysztof, Sun Li
Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment, Southeast University, Nanjing 210096, China.
Energy Electricity Research Center, International Energy College, Jinan University, Zhuhai 519070, China.
ISA Trans. 2022 Sep;128(Pt B):159-170. doi: 10.1016/j.isatra.2021.11.005. Epub 2021 Nov 18.
Safe and economic operation of an open-cathode proton exchange membrane fuel cell (PEMFC) requires an efficient thermal management strategy. The stack temperature regulation in PEMFC is, however, challenging due to often stringent set-point tracking tasks, frequent load fluctuations, constrained manipulated variables, and various modeling uncertainties and nonlinearities. To this end, a feed-forward offset-free model predictive control (MPC) approach, aiming at uncertainties resolving and disturbance mitigation, is developed to simultaneously address the above difficulties. In the proposed framework, the information about the measured power load fluctuations is used in the optimization algorithm as feed-forward information to eventually mitigate the influence of load fluctuations on the controlled output and increases the overall control quality. Additionally, the unmodeled dynamics and the other unmeasurable disturbances/uncertainties are collectively considered as an extended state of the system (to achieve zero static errors) and the on-line reconstructed aggregated disturbances is continuously sent to the MPC algorithm to increase its optimization performance and to achieve offset-free control objectives. The obtained results are quantitatively compared with conventional control strategies for PEMFCs, including a model-based PI controller, its modification utilizing disturbance feed-forward, and a standard offset-free MPC (i.e. without feed-forward). Both the simulations, realized in MATLAB/Simulink, and hardware experiments, conducted on a 500 W PEMFC testbed, show excellence of the proposed feed-forward offset-free MPC consisting in faster temperature tracking and higher robustness. The obtained satisfactory results show the introduced control solution to be a promising prospect and help accelerating further applications of PEMFCs.
开放式阴极质子交换膜燃料电池（PEMFC）的安全经济运行需要高效的热管理策略。然而，由于通常严格的设定点跟踪任务、频繁的负载波动、受限的操纵变量以及各种建模不确定性和非线性，PEMFC中的电池堆温度调节具有挑战性。为此，开发了一种旨在解决不确定性和减轻干扰的前馈无偏模型预测控制（MPC）方法，以同时应对上述困难。在所提出的框架中，将测量到的功率负载波动信息作为前馈信息用于优化算法，最终减轻负载波动对受控输出的影响并提高整体控制质量。此外，未建模动态以及其他不可测量的干扰/不确定性被共同视为系统的扩展状态（以实现零静态误差），并且将在线重构的总干扰连续发送到MPC算法以提高其优化性能并实现无偏控制目标。将获得的结果与用于PEMFC的传统控制策略进行定量比较，包括基于模型的PI控制器、利用干扰前馈的改进型以及标准无偏MPC（即无前馈）。在MATLAB/Simulink中实现的仿真以及在500W PEMFC试验台上进行的硬件实验均表明，所提出的前馈无偏MPC具有卓越的性能，包括更快的温度跟踪和更高的鲁棒性。获得的满意结果表明所引入的控制解决方案具有广阔的前景，并有助于加速PEMFC的进一步应用。
