Heavy-duty truck simulator: a tool to plan charging and charger layouts

Abstract

Digital Twins (DTs) and simulation tools are virtual representations of physical objects or processes that can collect information from the real environment to represent, validate, and replicate the physical twin’s present and future behaviour [1]. The aim of this thesis has been to gather the data requirements needed to prepare virtual tools capable of assessing mining sites, where traditional diesel-powered trucks are replaced by electric vehicles, with the organisation, analysis and incorporation of mining haul electric trucks in mines. This shift is driven by the need to reduce carbon emissions and improve sustainability in the mining sector. For the correct functioning of these virtual tools data requirements have to be recruited to make these tools work correctly. An iterative research method has been chosen for this, reviewing the improvements in each step until the desired result is achieved. The research method used begins with a comprehensive literature review to know which is the status of the electrification in mines in the actuality and the existence of related virtual tools. The following step was to determine which were the research questions and elaborate the corresponding experiments modifying the backbone code, iterating all the needed times. This thesis has explored the limitations in the existence of literature when referring to the simulation of mining heavy duty trucks in open pit mines, mostly due to the absence of real available data. Nevertheless, it has been demonstrated the potential of DTs and simulation models in optimizing the operation of electric mining fleets. The developed simulator provides a valuable tool for planning charging strategies, managing fleet sizes, and responding to dynamic environmental conditions. The study contributes to the goal of achieving efficient mining operations through the adoption of advanced digital technologies.