Swiss Federal Railways (SBB), Switzerland’s national railway operator, runs about 3,270 km of fully electrified standard-gauge track on 2024 figures, and Kathrein Solutions puts its daily load at 0.88 million travellers and 185,000 tonnes of goods. On a network worked that hard, an unplanned repair is never just one vehicle’s problem. A published case study from Kathrein Solutions, the German RFID hardware and software maker behind the readers, sets out how SBB closed the gap holding its condition monitoring back: it could tell that a vehicle was defective, but not which one.
The problem was never detection, it was identification
SBB Infrastructure operates the train inspection facilities and monitors the infrastructure and every vehicle running on it permanently. SBB says more than 100 train monitoring systems are in use across the network, measuring trains as they move for faults such as overheated braking systems, defective axle box bearings and load displacement, with the readings checked around the clock at an intervention centre in Erstfeld. The aim is to spot a defective vehicle early and intervene before it becomes an incident.
What was missing was real-time transparency at the level of an individual vehicle. SBB could establish that a vehicle was defective but could not determine its exact vehicle number, so condition measurements could not be passed to the vehicle owners responsible for acting on them, and nobody could use component wear data before the problem reached a critical level. The old process did catch defective vehicles once an intervention threshold was reached, but those unplanned interventions disrupted the transport chain and other traffic, hitting freight and passenger customers alike.
Reading each vehicle, axle by axle
The basis of the fix was vehicle identification using RFID transponders, which let data be assigned to a vehicle on an axle-by-axle basis. Only at that resolution can a vehicle’s condition be tracked reliably across several train control units, so a developing fault shows up as a trend rather than as a sudden threshold breach.
In service, vehicle axles are detected by rail contacts installed on the track. Linking that axle data with the RFID read generates a business event carrying both the condition data and the individual vehicle data, which is what delivers real-time transparency on rail vehicle condition. Kathrein Solutions developed an app tailored to SBB that displays presence, vehicle number and axles on mobile devices, depicting each vehicle with each individual axle.
Trackside hardware that has to survive a Swiss winter
Transponders on the trains and readers installed in the track bed both need particular robustness against all weather, which is why the reader used was the Kathrein RAIN RFID Reader ARU 3500, designed for harsh environments. RAIN RFID is the industry’s name for passive UHF RFID, the long-range form in which a battery-free tag is powered by the reader’s own signal, so a tag bolted to a wagon needs no servicing of its own.
The ARU 3500’s internal antenna kept hardware costs down for single-track applications, where one reader does the whole job. For double-track detection, a second ARU 3500 is connected as a slave, and master and slave IDs configured on the main reader let each read be assigned to the right track. Kathrein equipped all of the train control facilities, approximately 70 locations, with RFID readers, and the rail vehicles were marked with an RFID tag in accordance with EN 17230. That standard, “Information technology – RFID in rail”, was published by CEN in November 2020 and sets out where tags sit on rolling stock, what data they carry and how trackside reads must perform, using UHF RFID to hold the European Vehicle Number electronically.
The performance requirement was blunt: every read had to deliver the vehicle number and the track number, reliably, across a speed range of 5 km/h to 180 km/h, in Swiss winter conditions including snow and heavy rain. In total, 68 detection points are distributed across the Swiss rail network, 14 of them single-track detections running one ARU 3500 and the rest double-track detections using the master and slave pair.
Getting the data to the people who own the vehicles
Once the readers have captured the data, Kathrein CrossTalk software transfers it to the app built for SBB, with each reading point sending to three servers: productive, backup and test. CrossTalk also integrates the RFID hardware into SBB’s leading system, and the CrossTalk Agent makes each reader able to report its own status data, so reader health is monitored centrally through an SBB internal system rather than by sending anybody to the track.
Planning, installation and commissioning of the RFID infrastructure was carried out by Enkom AG, a Swiss communications infrastructure and systems integration firm in Sursee that Kathrein acquired in 2016. Kathrein backed it with maintenance and support, and on key questions during the project.
From an identifier to a maintenance method
What began as RFID-based identification for the sake of transparency turned into a new quality management approach in infrastructure maintenance. Real-time data on component condition and the onset of wear works as a digital early warning system, flagging a repair before it becomes urgent, so maintenance can be planned precisely without risking the timetable. Kathrein’s benefit list runs from predictive maintenance and passenger safety to investment protection for rails, overhead lines and train components, all of which take the punishment when a defective vehicle stays in traffic, and cost reduction by avoiding unplanned and unnecessarily expensive repairs. The digitised data is visualised on a terminal showing exactly which rail vehicle has a problem, which removes a labour-intensive search.
“We see vehicle identification using RFID in Rail as an enabler technology that digitizes all processes that rely on a vehicle ID.” – Stefan Koller, Head of Train Control Systems, SBB AG
The tag does not do the maintenance; it supplies the one piece of data, a trustworthy vehicle ID, that every digital process downstream was waiting on. Kathrein does not date the rollout in its case study, so the figures above describe the installation as published rather than a timeline. More deployments of this kind sit in our case studies and vehicle tracking sections.
Read more at https://kathrein-solutions.com/de/case-studies/case-study-schweizerische-bundesbahnen-fahrzeugidentifikation-2
