Knorr-Bremse Rail Systems UK and Chiltern Railways have announced a 12-month extension to their groundbreaking low adhesion monitoring trial, allowing the project to continue through to August 2027 and capture a second autumn leaf fall season.
The initiative, which launched in August 2025, is providing the rail industry with an unprecedented understanding of wheel-to-rail adhesion by delivering real-time data on railhead conditions. Developed jointly by Knorr-Bremse and Chiltern Railways, with support from Angel Trains, the technology has been installed on a Class 165 unit operating on both the Chiltern Main Line and the London to Aylesbury route.
The trial is helping engineers accurately identify where low adhesion occurs, how conditions vary across the network, and what mitigation measures may be required. By extending the programme for a further year, the partners aim to strengthen the dataset, enhance the technology and increase industry engagement.
Transforming Understanding of Low Adhesion
Unlike conventional systems that only detect wheel slide or traction slip events, the Knorr-Bremse solution calculates actual wheel-to-rail adhesion values during braking events, including the critical moments before and after Wheel Slide Protection (WSP) activation.
This provides engineers with a detailed view of railhead conditions and a far more accurate measure of how slippery the track is in real-world operation.
John May, Digital Services Business Development Manager at Knorr-Bremse Rail Systems UK, said:
“Data collected through our railhead low adhesion monitoring system has the potential to provide rail industry customers with a much clearer understanding of not only when low adhesion has occurred, but also where it is happening and what action may be needed to address it.
“The success of the first year of the trial has demonstrated the value of real-time adhesion monitoring. The quality of the data collected means we can identify low adhesion hotspots and seasonal trends with a high degree of accuracy. Extending the trial will strengthen the dataset further and help demonstrate how this intelligence can support a more proactive approach to managing low adhesion.
“As the trial enters its second year, our team believes the technology has the potential to transform how low adhesion is understood and managed across the UK rail network, enabling smarter interventions, more targeted railhead treatment and improved operational performance during challenging seasonal conditions.”
Valuable Industry Insight
Since entering passenger service in September 2025, the instrumented Class 165 has continuously gathered adhesion, braking, wheel slide and traction performance data without affecting normal operations.
By February 2026, the train had travelled more than 45,000 miles and recorded over 500 wheel slide events alongside 850 traction slip events across a wide variety of operating conditions, including autumn leaf fall and adverse weather.
The system has enabled engineers to pinpoint low adhesion hotspots to within a few metres while also monitoring differences in adhesion performance between individual axles during braking.
The high-resolution information generated is also supporting wider industry research, including work undertaken by the Rail Safety and Standards Board's Adhesion Research Group (ARG).
Building Towards Predictive Low Adhesion Management
According to Chiltern Railways, significant progress has also been made in analysing the large volume of operational data collected and refining the user interface to make the information more accessible for operational teams.
Louis Schmandt, Technical Engineer at Chiltern Railways and project lead, said:
“In the last year, excellent progress has been made in processing and understanding the vast pool of data that has been captured as well as refining and tailoring the User Interface to better suit the needs of the end user. Data analysis is now possible at both at a high, network-wide level as well as for investigating incidents in detail."
“Individual parameters can be selected as required to obtain the required information. Adhesion hotspots have been identified in areas that were not previously considered by Chiltern and Network Rail and a lot of progress has been made in better understanding the kinematics behind low adhesion events - in particular in the milliseconds in the lead up to and immediately following a WSP activation.
“This is very much in line with the main objective of this initiative; to develop a model which acts as the industry’s primary means of predicting low adhesion risk at any location and given time throughout the year. The next challenge will be to build on this capability and enable the WSP system to proactively utilise this data to directly control the train’s response to low adhesion, thereby reducing dependence on infrastructure mitigation measures or driver behaviour.
“There is now a strong case to scale up this trial to include additional units both at Chiltern and across other networks. This would help demonstrate the full potential of this concept, both in terms of predicting low adhesion risk to aid operators and infrastructure managers in their decision making as well in providing further technical insight for incident investigations and informing delay attribution.”
With a second autumn season now included in the trial, the project is expected to provide one of the most comprehensive datasets ever collected on low adhesion conditions in Britain, potentially paving the way for predictive adhesion management and smarter railway operations across the network.
Image credit: Knorr Bremse
