Reliable Energy and Cost Efficient Traction system for Railway

Project Information

RECET4Rail

Grant agreement ID: 101015423

DOI

10.3030/101015423

Project closed

EC signature date 9 December 2020

Start date 1 December 2020

End date 30 September 2023

Funded under

• SOCIETAL CHALLENGES - Smart, Green And Integrated Transport

Total cost

€ 2 300 036,25

EU contribution

€ 2 300 036,25

Coordinated by

UNION DES INDUSTRIES FERROVIAIRES EUROPEENNES - UNIFE
Belgium

Periodic Reporting for period 2 - RECET4Rail (Reliable Energy and Cost Efficient Traction system for Railway)

Reporting period: 2022-06-01 to 2023-09-30

Summary of the context and overall objectives of the project

Rail is a fundamental service for modern societies and the backbone of a sustainable transport system. About the challenges, on top comes the pressure to reduce energy consumption, pollution and the consumption of other resources. Mastering the breakthrough developments of new technologies is of capital importance for the railway industry to deliver smart and efficient solutions.Indeed essential to the growth of the rail industry is the reduction of the overall life cycle exploitation costs of all rail sub-systems. The EU-funded RECET4Rail Project is important for the society because it will provide essential knowledge and competence that can lead the improvement to high technology readiness levels of Shift2Rail traction demonstrations on trains developed by Shift2Rail members. This collaboration paves the way for future key developments in fields such as digitalisation applied to traction, environmental sustainability (especially devising carbon-free traction systems) and reinforcement of standardisation to lower complexity and costs. The Project will provide essential knowledge that will lead to future improvement of the high TRL level S2R traction demonstrations on trains done by the S2R Members, preparing future S2R key work on domains as digitalisation applied to Traction, environmental sustainability or reinforcement of standardisation to lower complexity and costs. The global rail sector must increasingly rely on the emerging disruptive technologies such as advanced robotics, 3-D printing, high computing power and connectivity, etc., which are integrated with analytical and cognitive technologies that enable machine-to-machine (M2M) and machine-to-human (M2H) communication. Therefore, mastering the breakthrough developments of new technologies is of capital importance for the railway industry to deliver smart and efficient solutions that improve safety, security, punctuality, availability, accessibility, seamless operation, capacity, connectivity, sustainability and other performances, while remaining economically affordable for everybody in countries all around the world. Indeed, essential to the growth of the rail industry is the reduction of the overall life cycle exploitation costs of all rail sub-systems, the minimisation of the effects of obsolescence and the effective migration of emerging technological innovation.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

During the 2RP, the project showed progress across various facets.

In WP1, objectives were met, but challenges arose in the timely execution of Model- Driven Optimization (MDO) and subsequent processes. Consequently, an amendment was pursued, securing project extensions and budget adjustments. The focus remains on achieving optimal outcomes through a Design of Experiment approach. WP2 faced unforeseen technical complexities and resource constraints. However, strategic problem-solving ensured the successful completion of deliverables for the 2nd Reporting Period, aligning with broader project objectives. In WP3, all main objectives for the reporting period were achieved. Minor deviations occurred, notably in the extended duration of humidity tests. To address this, testing was extended beyond the project's conclusion to extract maximum value from valuable samples.
WP4 witnessed achievements in the development of a method for cost-efficient maintenance schedules for multi-component systems. AALTO and ARAMIS modelled dependencies as a directed graph, facilitating systematic decision-making. Collaboration with POLIMI and RISE enhanced Prognostics and Health Management (PdM) approaches. Throughout the project, WP5 diligently focused on disseminating results widely and ensuring effective exploitation by target groups. This commitment underscores the project's broader impact beyond research activities.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

The efficient management of common consortium activities and the effective coordination of the project were insured during period 2 (WP6).

WP1 has reached all its main objectives for the RP2 reporting period. However, some risks and deviations incurred, and they are detailed in the appropriate chapter together with the mitigation measures applied. The time to perform MDO to find the optimal geometry and then print it, post process it and perform the tests might be off the actual deadline of the project. Thus, the real size module might be tested with the optimal geometry found by design of experiment instead of coming from the MDO. This deviations and risks brought to the need of having an amendment where project extension and budget shifts have been requested and approved.
WP2 has reached all its main objectives for the RP2 reporting period as well as within the broader project scope. Despite facing challenges, such as unforeseen technical complexities or resource constraints, strategic problem-solving ensured the fulfilment of goals. However, it's worth mentioning that submitting the deliverables planned for the 2nd Reporting Period posed a notable challenge. Despite encountering hurdles, WP2 ultimately led to the successful completion of the deliverables.
WP3 has reached all its main objectives for the RP2 reporting period. The activities have been carried out as planned and the was only a deviation “Humidity tests take much longer than expected and planned for” and the mitigation measure applied has been to continue with the testing beyond the end of the project to squeeze out the most from the valuable samples.
WP4 has reached all its main objectives for the RP2 reporting period. In specific: AALTO and ARAMIS finalized the development of a method for determining cost-efficient maintenance schedules for multi-component systems in the presence of economic and structural dependencies between components. Specifically, the dependencies are modeled as a directed graph whose nodes represent maintenance actions, arcs depict structural dependencies, and weights attached to arcs represent the costs of corresponding maintenance actions. AALTO and ARAMIS developed a method for a systematic and rationale decision making on the selection of the AI algorithms to guide the PHM analysts toward the solutions with the largest expected performance. ARAMIS, POLIMI and RISE enhanced the development of PdM approaches.
WP5 aimed to ensure that the project results & outputs are disseminated widely and effectively exploited by their target groups.

The project has demonstrated commendable progress and achievements across various WPs. Efficient management and coordination during period 2 (WP6) ensured the execution of common consortium activities. While WP1 encountered risks and deviations, strategic mitigation measures were applied, necessitating a project extension and budget shifts. WP2 faced challenges, including technical complexities and resource constraints, yet the team's problem-solving approach led to the successful completion of goals within the broader project scope. WP3 achieved its objectives, with only a deviation in humidity test duration, addressed by extending testing beyond the project's end. WP4 showcased significant accomplishments, with AALTO and ARAMIS developing methods for cost-efficient maintenance schedules and systematic decision-making on AI algorithm selection. PdM approaches were enhanced by ARAMIS, POLIMI, and RISE. Throughout the project, WP5 played a crucial role in disseminating results and ensuring effective exploitation among target groups.

Brochure of the Project RECET4Rail