E-RailOpt: an integrated energy modelling and optimisation tool for charging infrastructure placement in battery-electric freight rail

This study develops a comprehensive energy consumption model for freight battery-electric trains, explicitly accounting for factors often neglected in prior research, such as horizontal curvature resistance and regenerative braking. The model is formulated in the time domain, where train movement is simulated at one-second intervals, and spatially defined inputs—including vertical gradient, horizontal curvature, and speed limits—are interpolated into continuous temporal functions through a two-step integration process. The approach captures realistic train dynamics by iteratively determining acceleration, cruising, and braking phases based on route conditions and stopping requirements. The validated model is integrated with an optimisation algorithm and implemented within a Python-based, web-accessible decision-support tool. This integrated platform enables users to assess alternative charging strategies and optimise the spatial placement of charging or battery-swapping stations. A case study of the Sydney–Dubbo freight corridor demonstrates the applicability of the tool and highlights the operational feasibility and infrastructure requirements of battery-electric freight train deployment in Australia. The developed tool can be readily extended to other corridors and technologies, supporting data-driven policy and investment decisions in sustainable rail operations.