Actual-time modeling of a subway vehicle and optimal driving management with GA and ABC algorithms

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dc.authoridARIKAN YILDIZ, Yagmur/0000-0003-0947-2832
dc.contributor.authorArikan, Yagmur
dc.contributor.authorSen, Tolga
dc.contributor.authorCam, Ertugrul
dc.date.accessioned2025-01-21T16:35:27Z
dc.date.available2025-01-21T16:35:27Z
dc.date.issued2022
dc.departmentKırıkkale Üniversitesi
dc.description.abstractThe optimization of operations of subway systems has critical importance in terms of energy efficiency and costs. Therefore, driving management of subway vehicles has been gaining more importance day by day. Optimal Driving Management (ODM) is the optimization of the velocity trajectory of a subway vehicle by considering operating conditions and travel time. In this study, the driving of a subway vehicle has been modeled dynamically with all parameters that affect driving. So, a realistic model has been prepared. Then, a new objective function has been proposed to reduce energy consumption by using the subway vehicle's acceleration and braking forces parameters for ODM. The Artificial Bee Colony algorithm (ABC) and Genetic algorithm (GA) have been used on the prepared model to determine the driving dynamics of the subway vehicle. The performance of the algorithms has been evaluated in the real line network, which has multiple stations with different characteristics. The energy consumption has been reduced by 10.47% in GA and 8.92% in ABC compared to the actual driving values. Moreover, the results of the study have been analyzed in terms of passenger comfort, cost, and emission values.
dc.identifier.doi10.36909/jer.10205
dc.identifier.endpage218
dc.identifier.issn2307-1877
dc.identifier.issn2307-1885
dc.identifier.issue4A
dc.identifier.startpage204
dc.identifier.urihttps://doi.org/10.36909/jer.10205
dc.identifier.urihttps://hdl.handle.net/20.500.12587/24131
dc.identifier.volume10
dc.identifier.wosWOS:000891783100012
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.language.isoen
dc.publisherAcademic Publication Council
dc.relation.ispartofJournal of Engineering Research
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241229
dc.subjectDynamic model; Energy efficiency; Energy consumption; Artificial bee colony algorithm; Genetic algorithm
dc.titleActual-time modeling of a subway vehicle and optimal driving management with GA and ABC algorithms
dc.typeArticle

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