Abstract
The global focus on the role of hydrogen energy in achieving carbon neutrality is increasing, particularly in transportation. Establishing and operating hydrogen refueling stations for fuel cell vehicles (FCEVs) are gaining prominence. This study proposes a model-based fault detection algorithm to enhance safety at large-capacity liquid hydrogen (LH2) refueling stations. First, the LH2 refueling system is modeled using Aspen HYSYS, estimating the heat transfer coefficient of the storage tank to meet the normal evaporation rate (NER) specification of 0.9%. Second, diverse fault scenarios are identified via a Hazard and Operability study (HAZOP), and simulation data are generated for the normal and fault scenarios. Finally, a fault detection algorithm utilizing the cumulative summation (CUSUM) is developed, with its threshold determined by risk levels analyzed in HAZOP. This allowed for tighter fault detection as risk levels increased. The algorithm successfully identified faults for all 11 scenarios.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
