4.7 Article

Hydrogen station in situ back-to-back fueling data for design and modeling

期刊

JOURNAL OF CLEANER PRODUCTION
卷 329, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2021.129737

关键词

Hydrogen refueling station; Multiple refueling processes; Back-to-back; Hydrogen station demand; Fueling evaluation

资金

  1. U.S. Department of Energy [DE-EE0005890]
  2. National Science Foundation CREST Center for Energy and Sustainability funding [NSF1547723]
  3. PON RI 2014-2020 for Innovative Industrial PhD - European Union [CUP H25D18000120006, DOT1305040]
  4. Italian Ministry of Education, University and Research (MIUR)

向作者/读者索取更多资源

Hydrogen technologies are rapidly spreading, with a focus on developing a robust fueling infrastructure for the mobility sector. New hydrogen stations operating under extreme conditions require more informed designs and equipment to meet growing demand and frequent utilization. Experimental research and data analysis from Cal State LA Hydrogen Research and Fueling Facility can provide valuable insights for station performance modeling tools.
Hydrogen technologies are rapidly spreading, with significant attention to the mobility sector requiring a robust and widespread fueling infrastructure. Hydrogen stations are indeed fundamental to transitioning from pilot projects towards large-scale implementation in many countries. Operating under extreme conditions, the new stations need more informed designs and equipment to meet the growing demand and their more frequent utilization. Via a set of experimental research activities and investigated scenarios carried out at the Cal State LA Hydrogen Research and Fueling Facility, this paper shares a novel and comprehensive set of data collected over a period of one year on fueling events frequency and refueling process station behaviors. A performance evaluation of the station is presented under different load scenarios in severe conditions during back-to-back fuelings, with monitoring of fundamental parameters for infrastructure sizing, including dynamic cooling response, pressure levels, thermodynamics, and the state of charge of the vehicle. The presented data analysis could surely contribute as closer-to-reality inputs for a variety of station performance modeling tools.

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