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Energy usage optimisation of heavy haul freight trains

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dc.contributor.author Bogaers, Alfred EJ
dc.contributor.author Botha, N
dc.date.accessioned 2017-06-07T07:11:33Z
dc.date.available 2017-06-07T07:11:33Z
dc.date.issued 2016-10
dc.identifier.citation Bogaers, A.E.J. and Botha 2016. Energy usage optimisation of heavy haul freight trains. 10th South African Conference on Computational and Applied Mechanics (SACAM), 3-5 October 2016, Potchefstroom, South Africa en_US
dc.identifier.isbn 978-1-86822-673-3
dc.identifier.uri http://hdl.handle.net/10204/9180
dc.description 10th South African Conference on Computational and Applied Mechanics (SACAM), 3-5 October 2016, Potchefstroom, South Africa en_US
dc.description.abstract The aim of this paper is to outline a preliminary investigation into an energy optimisation model with the aim of eventually being incorporated into a real-time driver assist program. A significant portion of the South African economy is sustained by a large and extensive mining industry. Integral to sustaining the mining economy is the transport of mined raw material via freight rail over large distances, typically from the mines to central distribution or processing centres. Due to the heavy tonnage and long distances an enormous amount of energy is required. Using classical mechanics, an energy usage model for typical freight trains based on available tractive power and typical rolling stock resistances (curvature, friction, gravity etc) is considered. The aim is to find the optimal velocity profile over the full distance of the intended track for which the total locomotive energy usage is reduced. We will illustrate the robustness of the proposed model to predict optimal operational velocity profiles for a number of interesting scenarios, many supported by similarly related analytical studies. en_US
dc.language.iso en en_US
dc.relation.ispartofseries Worklist;18143
dc.subject Energy optimisation en_US
dc.subject Freight rail en_US
dc.title Energy usage optimisation of heavy haul freight trains en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Bogaers, A. E., & Botha, N. (2016). Energy usage optimisation of heavy haul freight trains. http://hdl.handle.net/10204/9180 en_ZA
dc.identifier.chicagocitation Bogaers, Alfred EJ, and N Botha. "Energy usage optimisation of heavy haul freight trains." (2016): http://hdl.handle.net/10204/9180 en_ZA
dc.identifier.vancouvercitation Bogaers AE, Botha N, Energy usage optimisation of heavy haul freight trains; 2016. http://hdl.handle.net/10204/9180 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Bogaers, Alfred EJ AU - Botha, N AB - The aim of this paper is to outline a preliminary investigation into an energy optimisation model with the aim of eventually being incorporated into a real-time driver assist program. A significant portion of the South African economy is sustained by a large and extensive mining industry. Integral to sustaining the mining economy is the transport of mined raw material via freight rail over large distances, typically from the mines to central distribution or processing centres. Due to the heavy tonnage and long distances an enormous amount of energy is required. Using classical mechanics, an energy usage model for typical freight trains based on available tractive power and typical rolling stock resistances (curvature, friction, gravity etc) is considered. The aim is to find the optimal velocity profile over the full distance of the intended track for which the total locomotive energy usage is reduced. We will illustrate the robustness of the proposed model to predict optimal operational velocity profiles for a number of interesting scenarios, many supported by similarly related analytical studies. DA - 2016-10 DB - ResearchSpace DP - CSIR KW - Energy optimisation KW - Freight rail LK - https://researchspace.csir.co.za PY - 2016 SM - 978-1-86822-673-3 T1 - Energy usage optimisation of heavy haul freight trains TI - Energy usage optimisation of heavy haul freight trains UR - http://hdl.handle.net/10204/9180 ER - en_ZA


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