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Conflict of Interest
In relation to this article, we declare that there is no conflict of interest.
Publication history
Received March 17, 2025
Revised July 28, 2025
Accepted September 4, 2025
Available online October 25, 2025
articles This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Enhanced Thermofl uidic Modeling and Open-Source Rigorous Simulation of Hydrogen Fueling Systems Validated with Real-World Data

Department of Chemical Engineering , Myongji University , 1Hydrogen Energy Solution Center , Institute for Advanced Engineering 2Korea Gas Safety Corporation
dongil@mju.ac.kr
Korean Journal of Chemical Engineering, October 2025, 42(12), 3055-3069(15)
https://doi.org/10.1007/s11814-025-00551-9

Abstract

The process of refueling Hydrogen Fuel Cell Electric Vehicles (HFCEVs) with compressed hydrogen gas faces two primary

challenges: the temperature rise in the vehicle tank and delay in fueling speed. Since most Hydrogen Refueling Stations

(HRSs) are addressing these challenges through cascade systems, there is a demand for performance evaluations of fueling

systems under various HRS confi gurations and operating conditions. However, there is a lack of generalized and validated

simulation codes, and experimental results are quite limited. In this study, we develop a model that can simulate real-world

fueling processes, including the cascade system, and conduct case studies based on actual HRS confi gurations. By implementing

a more detailed mathematical model than previous studies and simulation code for not only light-duty vehicles but

also heavy-duty vehicles, the developed model accurately and extensively simulates the fueling process for various operating

conditions and diverse types of vehicle tanks. The reliability of the developed model is validated using real-world data collected

from operational HRSs, including extreme operating conditions. The implemented code is available as open-source

and supports developing the confi guration and operation guidelines of HRSs to be built forward or running now.

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