Reference : Mixed hybrid and electric bus dynamic fleet management in urban networks: a model pre...
Scientific congresses, symposiums and conference proceedings : Unpublished conference
Engineering, computing & technology : Multidisciplinary, general & others
Computational Sciences
http://hdl.handle.net/10993/39910
Mixed hybrid and electric bus dynamic fleet management in urban networks: a model predictive control approach
English
Rinaldi, Marco mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
Picarelli, Erika mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
D'Ariano, Andrea mailto []
Laskaris, Georgios mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
Viti, Francesco mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
Jun-2019
Yes
6th International IEEE Conference on Models and Technologies for ITS
4-6 June 2019
Krakow
Poland
[en] Dynamic bus fleet management ; e-bus charging scheduling ; Model Predictive Control
[en] Abstract—Reducing pollutant emissions and promoting sustainable mobility solutions, including Public Transport, are increasingly becoming key objectives for policymakers worldwide. In order to jointly achieve these goals, careful consideration should be put on the operational cost and management of PT services, in order to promote the adoption of green mobility solutions and advanced management techniques by operators. In this work we develop a dynamic fleet management approach for next generation Public Transportation systems, considering the instance of mixed electric / hybrid fleet. Our objective is that of investigating to what extent electrification, coupled with optimal fleet management, can yield operational cost savings for PT operators, explicitly considering real-time disturbances, including delays, service disruptions etc. We propose a Mixed Integer Linear Program to address the problem of optimal scheduling of a mixed fleet of electric and hybrid / non-electric buses, and employ it as predictor in a Model Predictive Control approach. Test results based upon a real-life scenario showcase how the proposed approach is indeed capable of yielding a sizable reduction in operational costs, even when considerable disturbances arise from the underlying system.
Researchers ; Professionals ; General public
http://hdl.handle.net/10993/39910
FnR ; FNR11349329 > Francesco Viti > eCoBus > Electrified Cooperative Bus System > 01/07/2017 > 30/06/2020 > 2016

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