For the energy part, an energy simulation tool was developed by the complementary project OPEUS and was used by the FINE 1 project. Data was collected from technology developments of systems in different parts of Shift2Rail, and new Energy KPIs were calculated quantifying the overall progress. Regarding standardisation, the most suitable standard was selected, and the most essential KPIs were analysed, pointing to mass and sufficiency. A proposal for eco-labelling was also presented based on extensive stakeholder analysis. An analysis of future railway systems was performed considering future implementation of new technologies from S2R innovations as well as developments outside S2R and recommendations are indicating on research activities beyond S2R for further energy savings and CO2 reduction.
For the FINE1 energy consortium, a key strategic goal was to reinforce energy as a decision influencer in procurement decisions for rolling stock. For streamlined tender and project execution, a broadly accepted “protocol” was found in EN50591. The recently released norm EN50591 “Railway rolling stock – Specification and verification of energy consumption” is used as the basis for eco-labelling with regards to energy consumption. It defines broadly accepted and technically sound conditions, parameters, information to be produced and validation methods. To make sure the rail sector will use the eco-labelling, the strategy was to advertise both EN50591 approach (how to quantify energy) and the eco-label proposal (scheme how to structure/present the EN50591 information).
For the noise part, the most critical systems which are producing noise on rolling stock, as well as infrastructure in Shift2ail, were analysed and ranked. Several scenarios were defined combining rolling stock and infrastructure and after that also adding a traffic flow over 24h including, e.g. freight to form traffic scenarios. Targets were set, and improvements achieved by introducing noise control technologies developed was calculated at the end of the project. Therefore, the source ranking and system-level performance for the baseline was defined. In addition to assessments of progress, also tools and methodologies to support the development of efficient noise reduction technologies were performed primarily for interior noise. Sound propagation and distribution around typical train carbody structures were treated with extensive simulations, and testing campaigns and recommendations about preferred methods were included. Analysis of current methodologies for sources characterisation and proposals for improvements were delivered. Airborne, as well as structure-borne sound, was considered.
