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Joint optimal vehicle and recharging scheduling for mixed bus fleets under limited chargers
Chalmers Univ Technol, Dept Architecture & Civil Engn, S-41296 Gothenburg, Sweden..
Chalmers Univ Technol, Dept Architecture & Civil Engn, S-41296 Gothenburg, Sweden..
Beihang Univ, Minist Educ, Key Lab Intelligent Transportat Technol & Syst, Beijing 100191, Peoples R China.;Beihang Univ, Sch Transportat Sci & Engn, Beijing 100191, Peoples R China..
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport planning.ORCID iD: 0000-0002-2141-0389
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2023 (English)In: Transportation Research Part E: Logistics and Transportation Review, ISSN 1366-5545, E-ISSN 1878-5794, Vol. 180, article id 103335Article in journal (Refereed) Published
Abstract [en]

Owing to the high acquisition costs, maintenance expenses, and inadequate charging infrastructure associated with electric buses, achieving a complete replacement of diesel buses with electric counterparts in the short term proves challenging. A substantial number of bus operators currently find themselves in a situation where they must integrate electric buses with their existing diesel fleets. Confronted with the constraints of limited electric bus range and charging infrastructure, the primary concern for bus operators is how to effectively utilize their mixed bus fleets to adhere to pre-established bus timetables while maximizing the deployment of electric buses, known for their zero pollution and cost-effective travel. Consequently, this paper introduces the concept of the joint optimization problem for vehicle and recharging scheduling within mixed bus fleets operating under constrained charging conditions. To tackle this issue, a mixed integer linear model is formulated to optimize the coordination of bus schedules and recharging activities within the context of limited charging infrastructure. By establishing a set of feasible charging activities, the problem of electric buses queuing for charging at constrained charging stations is transformed into a linear optimization model constraint. Numerical simulations are conducted within the real transit network of the Dalian Economic Development Zone in China. The results indicate that the judicious joint optimization of vehicle and charging scheduling significantly enhances the service frequency of electric buses while reducing operational costs for bus lines. Notably, the proportion of total trips performed by electric buses rises to 80.4%.

Place, publisher, year, edition, pages
Elsevier BV , 2023. Vol. 180, article id 103335
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Transport Systems and Logistics
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URN: urn:nbn:se:kth:diva-340900DOI: 10.1016/j.tre.2023.103335ISI: 001108039000001Scopus ID: 2-s2.0-85175460027OAI: oai:DiVA.org:kth-340900DiVA, id: diva2:1820542
Note

QC 20231218

Available from: 2023-12-18 Created: 2023-12-18 Last updated: 2023-12-18Bibliographically approved

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