Our research project on intelligent rail head lubrication has shown what is technically possible when lubrication is controlled on the basis of real operational data.
Now the topic has entered the professional debate.
In the issue of ZEVrail, a detailed technical article has been published. The article presents the joint project carried out by BERNMOBIL, Substring and PROSE, funded by the Swiss Federal Office of Transport (BAV), and describes:
The concept of demand-driven rail head lubrication
Acoustic monitoring across 15 tram vehicles
AI-based evaluation of audio, meta and weather data
Predictive triggering of lubrication based on noise mapping
The transition from static lubrication to data-driven system control
What began as a research question “How to reduce curve squeal and wear with minimal use of lubrication agents?” has evolved into a validated, scalable system approach.
The publication shows that intelligent rail head lubrication is becoming part of the technical conversation about sustainable urban rail operations.
