Net Power Optimization Based on Extremum Search and Model-Free Adaptive Control of PEMFC Power Generation System for High Altitude

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The operating characteristics of proton exchange membrane fuel cell (PEMFC) generation systems will change in high altitude. In order to improve the system output performance, this paper proposes a net power optimization (NPO) based on extremum search and model-free adaptive control (MFAC) of PEMFC power generation system. A PEMFC power generation system model for high-altitude environment is established, the off-line analysis shows that with the increase of altitude, the performance of the air compressor decreases, the optimal oxygen excess ratio (OER) of the system decreases, and surge phenomenon is more likely to occur. Considering the non-minimum phase characteristic of the net power to OER, the OER is optimized online by extremum search strategy and the optimization step and cycle ensure the convergence of the strategy. Combined with a model-free adaptive control strategy based on compact form dynamic linearization (CFDL), the optimal OER is tracked real time, the data model identified online ensures the adaptability of the system. Finally, a hardware-in-the-loop platform is built and comparative experiment is carried out. The results show that: compared with the off-line optimization method (OOM), (1) NPO can improve the net power of the system at different altitudes through the adaptive adjustment of OER and no off-line data is required inappropriate static operating points are avoided. (2) in high altitude areas, NPO has higher operational stability and can effectively avoid surge phenomenon.