Trolley-Assisted Charging for Full-Shift Operation of Battery-Electric Load-Haul-Dump in Underground Mining
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Abstract
Underground mining operations are transitioning to battery-electric fleets to reduce diesel emissions and ventilation requirements. However, current battery technology cannot sustain a full production shift in battery-electric load--haul--dump (LHD) vehicles, forcing mid-shift charging stops or battery swaps that disrupt production. Trolley-assisted systems (TAS) address this limitation by supplying external power along selected route segments through two complementary mechanisms: dynamic charging, in which an overhead catenary delivers energy while the vehicle travels, and static connection, in which the LHD connects to the trolley rail during brief scheduled stops, such as dumping. Together, these mechanisms reduce net battery discharge and extend battery autonomy without dedicated charging downtime. This paper presents a simulation-based framework to quantify the operating capability of TAS-equipped LHDs and evaluate trolley-length allocation at the production level. A physics-informed power and energy model, built on the Sandvik LH518iB architecture, is integrated into a route-level simulator that reproduces a full draw-control schedule on a real Chilean copper mine layout. The trolley length is treated as a configurable design parameter and systematically varied to assess its effect on battery autonomy, idle time, and throughput. Results show that TAS can eliminate mid-shift battery swaps, improve productivity relative to battery-electric operation without TAS, and reduce energy cost per ton by up to 75 % compared with diesel operation. Furthermore, route-to-route energy variability motivates a two-stage stochastic optimization framework to determine routing and charging strategies for a given trolley configuration.
How to Cite
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Load-Haul-Dump, Trolley-Assisted Systems, Battery Electric Vehicles, Underground Mining, Stochastic Optimization, Energy Management
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