Keywords: freight train, monitoring, system architecture, model based system engineering, accident prevention, safety equipment, machine learning.

Lately the world of passenger rail transport has undergone profound changes that have brought rail back to the centre of both policy and market attention. However, rail is now facing another revolution: policies are pushing toward a modal shift for freight as well, hoping to increase rail modal share by tapping into a larger pool of freight (e.g. refrigerated goods) and make it more sustainable both on an environmental and social level. To fulfil this purpose, freight trains must take advantage of existing high-speed infrastructure designed for promiscuous use, but only used for passengers. A necessary condition toward this goal is for the trains to be equipped with monitoring systems that enable the rolling stock to be continuously diagnosed in order to increase their safety, quality, and reliability. In this paper, after providing an overview of the Technical Specification for Interoperabilities applied on passenger trains in Europe and of the needs of the freight market, an innovative monitoring system for the next generation high-speed freight electric multiple unit is designed with a model based systems engineering approach, defining functional, logical and physical architectures. Then its future technological implications are evaluated, in a context where artificial intelligence is increasingly central in all industries, especially in predictive maintenance.

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