Electric vehicles can be perceived as a means to achieve carbon reduction, energy efficiency, and sustainable development of the transportation industry. Electric vehicle sales and deployment are increasing rapidly over time. However, electric vehicle deployment should be conducted in a planned manner, as electric vehicles have some limitations (e.g., limited driving range, refueling capacity, carrying capacity). The electric vehicle scheduling problem should be studied in detail to overcome such limitations, as it addresses them while optimizing the paths and timetables of electric vehicles. A number of studies have been dedicated towards electric vehicle scheduling. Yet, there is a lack of survey studies that cover a structural recapitulation of the electric vehicle scheduling efforts and provide a thorough overview of the existing tendencies, operations research aspects, problem-specific properties, and future research needs. For this reason, this study offers a structured survey of the existing research studies, which assessed electric vehicle scheduling. The collected studies are grouped into three categories for a detailed review, namely general electric vehicle scheduling, electric vehicle scheduling with power grid considerations, and electric vehicle scheduling with environmental considerations. A detailed description of the relevant studies along with a summary of findings and future research needs are provided for each of the study categories. In addition, a representative mathematical model is outlined for each study category in order to guide the future research. The outcomes of this research are expected to provide interesting and important insights to different groups of professionals in the field of electric vehicles.

Electric vehicle scheduling: State of the art, critical challenges, and future research opportunities

Roshani A.;
2024-01-01

Abstract

Electric vehicles can be perceived as a means to achieve carbon reduction, energy efficiency, and sustainable development of the transportation industry. Electric vehicle sales and deployment are increasing rapidly over time. However, electric vehicle deployment should be conducted in a planned manner, as electric vehicles have some limitations (e.g., limited driving range, refueling capacity, carrying capacity). The electric vehicle scheduling problem should be studied in detail to overcome such limitations, as it addresses them while optimizing the paths and timetables of electric vehicles. A number of studies have been dedicated towards electric vehicle scheduling. Yet, there is a lack of survey studies that cover a structural recapitulation of the electric vehicle scheduling efforts and provide a thorough overview of the existing tendencies, operations research aspects, problem-specific properties, and future research needs. For this reason, this study offers a structured survey of the existing research studies, which assessed electric vehicle scheduling. The collected studies are grouped into three categories for a detailed review, namely general electric vehicle scheduling, electric vehicle scheduling with power grid considerations, and electric vehicle scheduling with environmental considerations. A detailed description of the relevant studies along with a summary of findings and future research needs are provided for each of the study categories. In addition, a representative mathematical model is outlined for each study category in order to guide the future research. The outcomes of this research are expected to provide interesting and important insights to different groups of professionals in the field of electric vehicles.
File in questo prodotto:
File Dimensione Formato  
Electric vehicle scheduling.pdf

accesso aperto

Tipologia: Documento in versione editoriale
Dimensione 4.08 MB
Formato Adobe PDF
4.08 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1235915
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 27
  • ???jsp.display-item.citation.isi??? 26
social impact