Holistic Modeling and Optimization of Hydrogen-Powered Trains for Zero-Emission Railway Operation

Abstract

This study introduces a comprehensive modeling framework for optimizing hydrogen-powered trains to facilitate zero-emission railway operations. Focusing on the Heidekrautbahn project in Brandenburg, Germany, the work addresses the unique challenges associated with hydrogen-powered trains by developing a modular python-based simulation environment. The approach enables easy and quick testing of operational strategies using simulative results before implementing only the most promising ones into actual operation. Four core components comprise the framework: (1) driving dynamics, (2) heating, ventilation, and air conditioning (HVAC), (3) energy management systems (EMS) and (4) hydrogen refueling processes. Collectively, the entire energy chain of hydrogen from refueling to traction force generation is represented. In this work, two key components, the driving dynamics and energy management modules, are validated using real-world measurement data from the Heidekrautbahn project. The sub-models are able to replicate the vehicle’s behavior, demonstrating high fidelity with errors below 5% compared to measurement. Leveraging the model, energy-saving potentials in the order of 10% for improved driving and energy management strategies were quantified. By means of simulationbased testing, efficient yet easy to implement operational strategies with increased range and flexibility are chosen. This research, conducted alongside the implementation, enhances the in-depth understanding of operation with hydrogen-powered trains, potentially improving their performance and positioning them as viable alternatives to traditional diesel-powered counterparts.