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The efficiency of a proton exchange membrane fuel cell system (PEMFCS), which includes a PEMFC stack and a dc/dc converter, depends on the applied voltage and there exists an efficiency extreme point (EEP) in PEMFCS. Therefore, the EEP of PEMFCS changes with varying load, because the system parameters are also varying. It makes EEP tracking (EEPT) a challenging assignment. In order to achieve the EEP operation of PEMFCS under varying load conditions without oscillation, this paper proposes a novel EEPT method based on a forgetting factor recursive least square (FFRLS) online identification. The FFRLS algorithm is based on data-driven and uses real-time data of the system to improve the estimation accuracy of PEMFCS parameters under the changing load. On the test bench of PEMFCS-battery system consists of 300-W PEMFCS, lithium-ion battery, PEMFC controller, and DSP controller, a multi-index performance test and comparative analysis were carried out. The results showed that the proposed method is not sensitive to load conditions. The performance of the proposed EEPT method for PEMFCS has been successfully validated. In addition, compared with the “perturb and observe” and “incremental conductance” online tracking algorithms, the proposed online identification method can get more satisfactory results. Such as, reducing the tracking time and hydrogen consumption, making the output power of PEMFCS smoother, which means its operation stress is smaller, and thus, it lasts longer.
Wang et al. (Tue,) studied this question.
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