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Productivity estimation of battery trolley mining truck fleets.
- Source :
- International Journal of Mining, Reclamation & Environment; Feb2024, Vol. 38 Issue 2, p144-166, 23p
- Publication Year :
- 2024
-
Abstract
- The mining sector is facing an immediate challenge to reduce its carbon emissions. The movement of material with mining truck fleets is a critical factor in reducing emissions. As the industry gradually replaces diesel trucks with more environmentally friendly transportation systems, it is important to analyse new solutions. This paper presents a new type of mining truck fleet called the Battery Trolley system, which is a combination of advanced technologies, including a battery-electric drivetrain, autonomy, trolley assist, and energy recovery systems. Depending on the site-specific differences and technology adoptions, decision-makers have three Battery Trolley system configurations to choose from: dynamic charging, stationary charging, and dual trolley Battery Trolley systems, each of which has its own advantages and disadvantages. One of the challenges of using Battery Trolley systems is their capacity and productivity. This study uses open-accessible project parameters and databases, with engineering assumptions, to create a mining scenario for both the dynamic charging and stationary charging perspectives. The study provides an equation to evaluate the Battery Trolley system's mining productivity. Results show an incremental analysis of the Battery Trolley productivity as the trolley power increases from 8 MW to 32 MW in various Battery Trolley configurations. The study compares the Battery Trolley productivity for several open-pit mining applications, including copper, iron, and overburden waste. The results indicate that: (i) trolley power limitations significantly affect the capacity of Battery Trolley systems; (ii) a stationary charging option can achieve higher capacity and productivity than dynamic charging; (iii) Battery Trolley productivity varies in different applications under the given simulation assumptions. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 17480930
- Volume :
- 38
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- International Journal of Mining, Reclamation & Environment
- Publication Type :
- Academic Journal
- Accession number :
- 175443432
- Full Text :
- https://doi.org/10.1080/17480930.2023.2278013