English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

As a highly nonlinear system, the performance of proton exchange membrane fuel cell (PEMFC) is controlled by various parameters. If the effects of all parameters are considered during the performance optimization, low working efficiency and waste of resources will be caused. The development of sensitivity analysis for parameters can not only exclude the parameters which have slight effects on the system, but also provide the reasonable setting ranges of boundary values for simulation of performance optimization. Therefore, sensitivity analysis of parameters is considered as one of the methods to optimize the fuel cell performance. According to the actual operating conditions of PEMFC, the fluctuation ranges of seven sets of parameters affecting the output performance of PEMFC are determined, namely cell operating temperature, anode/cathode temperature, anode/cathode pressure, and anode/cathode mass flow rate. Then, the control variable method is used to qualitatively analyze the sensitivity of main parameters and combines with the Monte Carlo method to obtain the sensitivity indexes of the insensitive parameters under the specified current density. The results indicate that among these parameters, the working temperature of the fuel cell is the most sensitive to the output performance under all working conditions, whereas the inlet temperature is the least sensitive within the range of deviation. Moreover, the cloud maps of water content distribution under the fluctuation of three more sensitive parameters are compared; the results verify the simulated data and further reveal the reasons for performance changes. The workload of PEMFC performance optimization will be reduced based on the obtained results.

Assessment of Sensitivity to Evaluate the Impact of Operating Parameters on Stability and Performance in Proton Exchange Membrane Fuel Cells