First Element Fuel
Process Optimization for Hydrogen Vehicle Refueling
We developed a comprehensive process model for liquid hydrogen distribution, focusing on Station Tank and Trailer subsystems. Validated using empirical data, the model enabled a detailed parametric study exploring performance optimization by varying station mass, pressure, and trailer offloading parameters. Employing machine learning techniques, we created predictive models for station consumption and refueling times. By integrating Google Maps traffic data, we implemented a just-in-time scheduling approach that optimizes trailer routes, enhancing the efficiency and reliability of the liquid hydrogen distribution network.
Team Members:
Jaideep Rao Alladi (Team Lead), Aaron Viren Buell, Junjie Zhang, Lezhou lyu, Yueran Guo
Project Deliverables:
- Prepare PRD, Subsystem Identification
- Steady State Process model development,
- Plan for Transient Analysis of the Model
- Transient Analysis Model Development
- Plan for optimization study
- Execution of optimization study
- Reports
