Zero-emission traction for rail

Abstract

Replacing the energy density and convenience of diesel fuel for all forms of fossil fuel-powered trains presents significant challenges. Unlike the traditional evolutions of rail which has largely self-optimised to different fuels and cost structures over 150 years, the challenges now present with a timeline of just a few decades. Fortunately, unlike the mid-1800s, simulation and modelling tools are now quite advanced and a full range of scenarios of operations and train trips can be simulated before new traction systems are designed. Full trip simulations of large heavy haul trains or high speed passenger trains are routinely completed controlled by emulations of human drivers or automated control systems providing controls of the “virtual train”. Recent developments in digital twins can be used to develop flexible and dynamic models of passenger and freight rail systems to support the new complexities of decarbonisation efforts. Interactions between many different traction components and the train multibody system can be considered as a system of systems. Adopting this multi-modelling paradigm enables the secure and integrated interfacing of diverse models. This paper demonstrates the application of the multi-modelling approach to develop digital twins for rail decarbonisation traction and it presents physics-based multi-models that include key components required for studying rail decarbonisation problems. Specifically, the challenge of evaluating zero-emission options is addressed by adding further layers of modelling to the existing fully detailed multibody dynamics simulations. The additional layers detail control options, energy storage, the alternate traction system components and energy management systems. These traction system components may include both electrical system and inertia dynamics models to accurately represent the driveline and control systems. This paper presents case study examples of full trip scenarios of both long haul freight trains and higher speed passenger trains. These results demonstrate the many complex scenarios that are difficult to anticipate. Flowing on from this, risks can be assessed and practical designs of zero-emission systems can be proposed along with the required recharging or refuelling systems.

Keywords

Locomotive / Virtual train / Simulation / Digital twin / Traction / Braking / Energy / Storage

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