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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. [ABSTRACT FROM AUTHOR] more...

Abstract The proton exchange membrane fuel cell (PEMFC) stacks are not widely used in the field of transportation industry, due to their limited power. Thus, the PEMFC stacks usually connected in parallel or series to meet the load demand power in high-power applications. The hydrogen consumption of multi-stack fuel cells (MFCs) system is related to the efficiency and output power. In addition, the efficiency of PEMFC depends on the applied voltage and other parameters. Consequently, the hydrogen consumption of system changes with varying load, because the system parameters are also varying. It makes reducing the fuel consumption of system a challenging assignment. In order to achieve the goal of minimizing fuel consumption of parallel-connected PEMFCs system, this paper proposes a novel power distribution strategy based on 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 PEMFC system parameters. On the test bench of parallel-connected PEMFCs system consists of two 300 W PEMFC stacks, PEMFC stack controller, DC/DC converters, and DSP controller etc. , a multi-index performance test and comparative analysis are carried out. The results showed that, the performance of proposed power allocation strategy has been successfully validated. In addition, compared with the power average and daisy chain algorithms, the proposed online identification power distribution method can get more satisfactory results. Such as, reducing the hydrogen consumption and improving efficiency. Highlights • FFRLS algorithm uses real-time data of the system to improve the estimation accuracy of PEMFC system parameters. • A multi-order equation is used to approach the minimum hydrogen consumption rate curve. • An online identification power distribution method is proposed to reduce the system consumption. • The proposed method could improve system efficiency and reduce the fuel consumption. [ABSTRACT FROM AUTHOR] more...