Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
A statistical operating cycle description for prediction of road vehicles’ energy consumption
Chalmers University of Technology, Sweden.
RISE - Research Institutes of Sweden, Safety and Transport, Safety.ORCID iD: 0000-0002-6730-0214
Chalmers University of Technology, Sweden.
Chalmers University of Technology, Sweden; VTI Swedish National Road and Transport Research Institute, Sweden.
Show others and affiliations
2019 (English)In: Transportation Research Part D: Transport and Environment, ISSN 1361-9209, E-ISSN 1879-2340, Vol. 73, p. 205-229Article in journal (Refereed) Published
Description
Abstract [en]

We propose a novel statistical description of the physical properties of road transport operations by using stochastic models arranged in a hierarchical structure. The description includes speed signs, stops, speed bumps, curvature, topography, road roughness and ground type, with a road type introduced at the top of the hierarchy to group characteristics that are often connected. Methods are described how to generate data on a form (the operating cycle format) that can be used in dynamic simulations to estimate energy usage and CO2 emissions. To showcase the behaviour of the description, two examples are presented using a modular vehicle model for a heavy-duty truck: a sensitivity study on impacts from changes in the environment, and a comparison study on a real goods transport operation with respect to energy usage. It is found that the stop intensity and topography amplitude have the greatest impact in the sensitivity study (8.3% and 9.5% respectively), and the comparison study implies that the statistical description is capable of capturing properties of the road that are significant for vehicular energy usage. Moreover, it is discussed how the statistical description can be used in a vehicle design process, and how the mean CO2 emissions and its variation can be estimated for a vehicle specification.

Place, publisher, year, edition, pages
Elsevier Ltd , 2019. Vol. 73, p. 205-229
Keywords [en]
CO2 emissions, Commercial vehicles, Hierarchical Markov model, Operating cycle, Road description, Stochastic road model, Carbon dioxide, Energy utilization, Fleet operations, Markov processes, Roads and streets, Stochastic systems, Topography, Truck transportation, Markov model, Road models, Stochastic models
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-39651DOI: 10.1016/j.trd.2019.07.006Scopus ID: 2-s2.0-85068800790OAI: oai:DiVA.org:ri-39651DiVA, id: diva2:1341043
Note

Funding details: Energimyndigheten; Funding details: Fellowships Fund Incorporated, FFI; Funding details: 44929-1; Funding text 1: The authors gratefully acknowledge financial support from the COVER project (44929-1), funded by the Swedish energy agency and the Swedish vehicle research and innovation programme (FFI).

Available from: 2019-08-07 Created: 2019-08-07 Last updated: 2019-08-16Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Johannesson, PärFast, Lars

Search in DiVA

By author/editor
Johannesson, PärFast, Lars
By organisation
SafetyElectronics
In the same journal
Transportation Research Part D: Transport and Environment
Natural Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
v. 2.35.7