Simulation-based evaluation of energy and operational efficiency for mine haul truck fuel alternatives
Keywords: CO2 emission, discrete-event simulation, alternative fuels, diesel substitution, surface mining
Abstract
The growing impact of climate change has prompted global efforts toward decarbonization, including ambitious targets set by the 2016 Paris Agreement. In the mining sector, the main contributors to greenhouse gas (GHG) emissions are loading and haulage, typically carried out using large diesel trucks. This study evaluates alternatives to diesel fuel for mining trucks, focusing on electricity, renewable diesel, and liquefied natural gas (LNG). Using discrete-event simulation (DES), we assessed these fuels based on operational data from an open-pit copper mine over a 24-hour period. Results reaffirm diesel as the current industry standard but highlight electric trucks as the most effective at reducing CO2 emissions by up to 95%, while also lowering operating costs. However, their success depends heavily on charging infrastructure and efficient energy management. Renewable diesel offers an approximately 90% reduction in CO2 emissions and is compatible with existing equipment, making it a viable transitional option for operations not yet ready for electrification. LNG, often promoted as a cleaner fuel, resulted in a 69% increase in fuel consumption and a 48% higher CO2 emissions in this study, questioning its role in decarbonization. Overall, renewable diesel and low-energy electric trucks appear to be the most promising paths toward greener mining. The optimal solution varies by site, depending on infrastructure, operational demands, and decarbonization goals. Further studies are needed to conduct a comparative analysis of different truck fuel types under varying mining conditions, including evaluations of cost-effectiveness and full environmental impact.
Más información
| Título de la Revista: | SIMULATION-TRANSACTIONS OF THE SOCIETY FOR MODELING AND SIMULATION INTERNATIONAL |
| Fecha de publicación: | 2026 |
| Idioma: | Ingles |
| URL: | https://journals.sagepub.com/doi/10.1177/00375497251412903 |