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Many solutions have been developed to reduce energy consumption in rail, covering the three main areas of rolling stock, infrastructure and operations. These solutions often show significant energy savings in theory, simulation and practice. However, the success of a solution can only be evaluated within the scope of the study performed, which is limited to specific case studies. Because railways vary greatly, a solution deemed effective when applied to one railway may not be well suited to another, due to inherent differences. This work therefore aims to develop a method to evaluate solutions for complex systems, using energy saving in rail as an example. Distinct subsystems are quantitatively defined by determining the factors that make them unique. For rail, these are categorised into route, vehicle and service characteristics. Next, key performance indicators are identified that relate to the success of solutions. Finally, a sensitivity analysis is performed to evaluate which factors influence solution success for each subsystem. In-depth simulations of solutions can then be completed. The developed method is used to find the most influential factors when considering energy-saving solutions applicable to single trains, for six types of railway subsystems, using Morris' elementary effects method of sensitivity analysis.

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