Real-time underground route identification and route progress using simple on-board sensing and processing
DOI:
https://doi.org/10.17159/Abstract
Conserving energy resources is emphasized globally. This emphasis led to the application of hybrid vehicle power systems. This study focuses on a hybrid underground train used in mines. Optimally applied hybrid systems can save up to 40% on fuel cost. To optimally manage a hybrid vehicle's energy flow it is necessary to know, in real-time, all the energy requirements to complete a route, mainly influenced by vehicle mass, vehicle speed profile and route topography. Of these three, the topographic profile is the only one that is only route dependent, and not influenced by the vehicle or driving styles. Another such route characteristic is the heading vs. distance profile. In this study the topographic and heading profiles are used to identify routes by and are easily measured by means of digital barometric pressure and compass sensors. Correlations between the current route and stored routes are performed based on their topographic and heading profiles in a point-by-point manner. Above ground tests were first performed using a road vehicle and 6 routes to evaluate the system. The system consistently correctly identifies routes within 20 % of the trip distance of ±20 km. The system proved to function correctly in underground tests through the implementation of an instrumented surveyor's wheel. This system finds direct practical application in optimizing the energy management of underground hybrid locomotives used by the mining industry in South Africa but can also be of benefit for applications where route identification is required and using GPS is not feasible.
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Copyright (c) 2024 Riaan Meeser, Nico Theron
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