Government funding for innovations that “could revolutionise British rail travel”

Working with COLAS Rail, the team will demonstrate high energy-density fuel cells and a carbon neutral bio-liquid petroleum gas fuel system to power auxiliary electric power requirements which account for up to 10-15% of the total power demand on freight trains, covering engine and traction motor cooling, safety and signalling systems and locomotive control systems. This will remove the need for diesel powertrains to remain powered up or idling during dwell times, which can cause up to 20% of freight locomotive fuel consumption and emissions.

Working with OpenTrainTimes, Pragmatex, Network Rail, Eddie Stobart and Solent Stevedores, an innovative freight planning solution (PathPlanner) will improve the planning process to reduce the time required to find new freight paths (slots in the timetable which can accept a freight train) into and out of their port at Southampton, thus increasing capacity and allowing the transfer of containers from HGVs to trains.

Working with Steer, Eversholt Rail, FedEx, Network Rail and DHL, the team will transform high-speed rail logistics combining a repurposed all electric passenger unit with adapted containerised consignment devices to support the conveyance of parcels, which is new to rail. This technology, offering a new approach to using space at stations to create easily accessible city-centre distribution hubs, will enable the operation of a new high-speed non-letters parcels service.

Supported by Great British Railways Transition Team and Network Rail, the project will focus on giving freight teams a bespoke and novel system that will automatically calculate conflicts in access rights against the timetable and real-world operational working, and enable freight operators to spot bid for access to the rail system.

Working with LB Foster, GB Freight and Eversholt Rail Group (ERG), the team will design and manufacture a self-powered semi-autonomous bogie which will improve operating flexibility as it can move one or twenty containers, operated by one person, who can then divide and track the containers to different locations, saving time, reducing noise pollution, and improve air quality both within the terminal and in the wider community.

With support from the University of Sheffield, UniPart Rail, KT Precision Engineering Ltd, PCB Train, Techni Measure Ltd and Murgitroyd, European Patent & Trade Mark Attorneys, National Research Council Canada, L.B. Foster Rail Technologies, the team aims to further develop and demonstrate a small under-rail sensor that reports key rail and freight vehicle operating parameters with system benefits such as reducing possession duration, reducing inspection/maintenance downtime and providing rail operators with easy access to the data streams.

Working with British Solar Renewables, University of York, Network Rail, DB Schenker, and East Coast Mainline operators, the project will provide the research, development and pilot for installation and testing of a prototype converter on the East Coast Mainline, making renewable energy compatible with powering UK railways.

Supported by Transport Design International, Horiba Mira and DB Cargo, the team aims to demonstrate its XNO battery chemistry for certain classes of battery electric trains. Specifically, it aims to demonstrate its suitability for passenger trains that can be powered by the AC overhead electrification and charge a battery from the overhead wire (or another form of ‘standard’ trackside power, eg third rail), to then run in battery-only mode on unelectrified sections of a route.

Working with VOLTSPORT, CLEC and HS2, the team’s solution covers the development of an electric motor and battery system, with controller, using commercially available products, which can be retrofitted into existing construction plant, replacing the traditional diesel engine with a quieter, cleaner, zero emissions drivetrain. These pieces of plant and equipment will be used as direct replacements for diesel machines in the construction and maintenance of railway infrastructure.

Working with the University of Nottingham, Atkins SNC Lavalin and Angel Trains, the team will provide a solution to substantially reduce emissions when diesel passenger trains are idling by developing and integrating a small, low mass, yet high peak torque and peak power, axle mounted motor, for retrofit and upgrade for passenger vehicle applications. This motor will enable kinetic energy recovery during braking and also provide power to the wheels whilst accelerating, reducing the emissions generated.

Supported by Angel Trains, the team will provide a solution to substantially reduce emissions when diesel passenger trains are idling by externally powering ancillary loads, such as heating, ventilation and air conditioning, door control and lighting with a low-cost, automated energy supply connected to the third rail.

Working with PENDYNE, EMINOX and East Midland Railway, the team will develop a new exhaust gas heating solution with the capability to dramatically improve the effectiveness of the exhaust after-treatment system in covered stations. The technology is a development of an electrically heated catalyst which has been used in road applications but is entirely new to rail and could unlock the in-station benefits of after-treatment systems on diesel trains.

Working with the University of York, Network Rail, West Coast Mainline operators and Angel Trains, the team will install a novel charging solution enabling charging fed from existing standard local power supply cables. Compatible with all OLE-powered trains, the small, low-cost design enables the removal of diesel passenger train operation on routes without continuous electrification.

Working with Northern Trains, Leeds Rhinos Rugby League Club, West Yorkshire Combined Authority, Leeds City Council, In The Round and Avanti West Coast, the team will demonstrate a solution for accurately predicting rail demand for a series of large visitor events, generating advance insight on rail capacity, and enhancing the ability of train operating companies to optimally plan and deliver timetables and services.

Working with Network Rail, Transport for Wales and LNER, the team will develop a timetable analysis system that will aggregate observed train movements against a line or route and compare them to typical planned timings. It will use this to calculate an “achievability score”, which will indicate what proportion of trains could be expected to run on time to that timetable, and calculate the minimum headway between consecutive services such that the following service does not have to slow down.

Supported by Angel Trains and Network Rail, this project will apply novel and innovative computer vision techniques to existing video footage to identify where extreme heat has affected the tension of overhead lines; and also install an ultraviolet camera to detect corona discharge as an early warning of potential electrical equipment failure caused by weather conditions. Both can then enable action to prevent assets failing and impacts on service, safety and customer experience.

Working with GTS, Focus Sensors and Network Rail, the team will demonstrate technology capable of delivering a persistent perimeter detection system that can detect persons approaching a site before they reach the perimeter boundary and alert railway staff to their precise location. This will support railway staff to respond effectively and reduce delay minutes, ensuring efficiency and cost benefits.

Supported by Network Rail, the team will explore the use of artificial intelligence and fuzzy logic powered real-time flow control to reduce flooding and associated damage. The Rail Flood Defender system uses low cost sensors and valves to monitor and control the flow of water inside rail drainage systems. This will provide real-time data to Network Rail, enable the storage volume in upstream pipes to be utilised to reduce downstream flood risk/volume, and enable the periodic flushing of drainage systems to remove blockages.

Working with Cranfield University and Network Rail, the team will develop an innovative algorithm to plan the route allocation of trains and schedule their maintenance, integrating a tool that can predict sand refilling (needed to aid adhesion to the track). This algorithm will be integrated into the scheduling software to plan train maintenance according to the need for replenishing sand. 

Working with Thales and Network Rail, the team will develop a technology solution, using existing trackside optical fibre cables, which can be used to locate cable thefts instantly to within a metre. After a theft is reported or detected by other systems, automatic analysis will pinpoint the location of the acoustic signatures of the theft activity. The location of the theft will be instantly displayed.  enabling police and security to be deployed sooner and more accurately.

Working with Transmission Dynamics Poland and supported by Angel Trains, Network Rail and West Midlands Trains, the team aims to integrate data from a range of Transmission Dynamics’ existing remote condition monitoring sensor solutions into NR’s monitoring and planning systems/processes, to enable more informed planning of infrastructure maintenance during possessions. 

Working with eviFile and Network Rail, the team will develop a product that will use optimisation and machine learning algorithms to identify potential optimal plans for possessions. Using wide-ranging railway possessions data the team will research and adapt algorithms that will consider (for example) multiple scenarios, locations and types of work, and optimise and efficiently manage resources to ensure minimal impact to infrastructure traffic and capacity.

Working with the University of Birmingham, Eurostar, Network Rail (NRHS) and Analog Devices, the team aims to overcome delays to line reopening or removal of speed restrictions by providing track engineers with the first ever portable dynamic track geometry measurement system. They will modify a permanent solution into a portable one that can be temporarily fixed to vehicles along with a lineside sensor array that can provide additional safety critical track information to the engineer. This solution will provide immediate track information to support informed decisions about the safety of the track and to what extent speed restrictions can be lifted or lines re-opened.

Working with Instrumental, Network Rail and Northern Trains, the team will provide standardised signalling asset sensor data to Network Rail in near real-time within an open commercial model, so that Network Rail will have ownership of the data, enabling them to implement new measures, identify bottlenecks within the network and target unexplained delay minutes in a way not currently possible. Data will also be available for use by train operators and the wider data analytics supply chain, removing some of the systemic blockers around access to data.