Using Data to Understand the Impact of Adhesion on Variability in Train Driving and Service Delivery

Using data to better understand variability in train driving and service delivery under different adhesion conditions.

Whilst some driving variability is expected during normal service, there is greater potential for significant variability in low adhesion due to the changing conditions. This can impact differences in how traction power is taken, maximum speed attained, and when and how the brake is applied when compared to good adhesion conditions. This presents an opportunity to seek more consistency to improve performance and safety.

Using data already captured by on-train systems it is possible to better understand the variation of how trains operate on the network during low adhesion conditions. Cross-referencing this with additional data sources such as the environmental and adhesion conditions, it is possible to determine perceived, expected and actual levels of adhesion during service and how this affects variability.

RSSB is working with West Midlands Train to collect on-train system data and other operational data during autumn 2018 relating to class 323s. This fleet works on the Cross-city line in Birmingham which regularly suffers from low adhesion during leaf-fall season, making it a perfect candidate to better understand the effects of adhesion on driver variability.

Indeed, RSSB are working in conjunction West Midlands Trains, Network Rail (LNW Route) and several suppliers on a suite of research projects to better understand the effects of low adhesion and the effect of mitigations, including enhanced sanders and rail treatments. Thanks to this work the rail industry will have a much deeper understanding of low adhesion, its effects and how to tackle it in the round.

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Aaron Barrett
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