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An enhanced stochas...
An enhanced stochastic operating cycle description including weather and traffic models
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- Romano, Luigi, 1994 (författare)
- Chalmers University of Technology, Sweden,Chalmers tekniska högskola
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- Johannesson, Pär (författare)
- RISE,Kemi och Tillämpad mekanik,RISE Research Institutes of Sweden, Sweden
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- Bruzelius, Fredrik, 1974- (författare)
- Statens väg- och transportforskningsinstitut,Förare och fordon, FOF,Chalmers University of Technology, Sweden; VTI Swedish National Road and Transport Research Institute, Sweden,Statens Väg- och Transportforskningsinstitut (VTI),The Swedish National Road and Transport Research Institute (VTI),Chalmers tekniska högskola
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visa fler...
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- Jacobson, Bengt J H, 1962 (författare)
- Chalmers University of Technology, Sweden,Chalmers tekniska högskola
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visa färre...
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(creator_code:org_t)
- Elsevier Ltd, 2021
- 2021
- Engelska.
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Ingår i: Transportation Research Part D. - : Elsevier Ltd. - 1361-9209 .- 1879-2340. ; 97
- Relaterad länk:
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https://doi.org/10.1...
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https://doi.org/10.1...
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https://research.cha... (primary) (free)
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https://urn.kb.se/re...
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https://doi.org/10.1...
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https://urn.kb.se/re...
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https://research.cha...
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Abstract
Ämnesord
Stäng
- The present paper extends the concept of a stochastic operating cycle (sOC) by introducing additional models for weather and traffic. In regard to the weather parameters, dynamic models for air temperature, atmospheric pressure, relative humidity, precipitation, wind speed and direction are included. The traffic models is instead based on a macroscopic approach which describes the density dynamically by means of a simple autoregressive process. The enhanced format is structured in a hierarchical fashion, allowing for ease of implementation and modularity. The novel models are parametrised starting from data available from external databases. The possibility of generating synthetic data using the statistical descriptors introduced in the paper is also discussed. To investigate the impact of the novel parameters over energy efficiency, a sensitivity analysis is conducted with a combinatorial test design. Simulation results show that both seasonality and traffic conditions are responsible for introducing major variations in the CO2 emissions. © 2021 The Author(s)
Ämnesord
- NATURVETENSKAP -- Geovetenskap och miljövetenskap -- Meteorologi och atmosfärforskning (hsv//swe)
- NATURAL SCIENCES -- Earth and Related Environmental Sciences -- Meteorology and Atmospheric Sciences (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Samhällsbyggnadsteknik -- Transportteknik och logistik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Civil Engineering -- Transport Systems and Logistics (hsv//eng)
- SAMHÄLLSVETENSKAP -- Social och ekonomisk geografi -- Ekonomisk geografi (hsv//swe)
- SOCIAL SCIENCES -- Social and Economic Geography -- Economic Geography (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Naturresursteknik -- Annan naturresursteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Environmental Engineering -- Other Environmental Engineering (hsv//eng)
- NATURVETENSKAP -- Geovetenskap och miljövetenskap -- Miljövetenskap (hsv//swe)
- NATURAL SCIENCES -- Earth and Related Environmental Sciences -- Environmental Sciences (hsv//eng)
Nyckelord
- Autoregressive models
- CO2 emissions
- Operating cycle
- Stochastic modelling
- Traffic description
- Transport mission
- Weather description
- Atmospheric humidity
- Atmospheric pressure
- Carbon dioxide
- Energy efficiency
- Sensitivity analysis
- Stochastic models
- Wind
- Auto regressive models
- CO$-2$/ emission
- Stochastic-modeling
- Stochastics
- Traffic modeling
- Weather modeling
- Stochastic systems
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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