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Development of the Vastra Gotaland operating cycle for long-haul heavy-duty vehicles
Chalmers University of Technology, Sweden.
RISE Research Institutes of Sweden, Material och produktion, Kemi och Tillämpad mekanik.ORCID-id: 0000-0002-9586-8667
RISE Research Institutes of Sweden, Material och produktion, Korrosion.ORCID-id: 0000-0002-6730-0214
Chalmers University of Technology, Sweden.
Vise andre og tillknytning
2023 (engelsk)Inngår i: IEEE Access, E-ISSN 2169-3536, Vol. 11, s. 73268-Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

In this paper, a complete operating cycle (OC) description is developed for heavy-duty vehicles traveling long distances in the region of Västra Götaland, Sweden. Variation amongst road transport missions is accounted for using a collection of stochastic models. These are parametrized from log data for all the influential road parameters that may affect the energy performance of heavy trucks, including topography, curvature, speed limits, and stop signs. The statistical properties of the developed OC description are investigated numerically by considering some composite variables, condensing the salient information about the road characteristics, and inspired by two existing classification systems. Two examples are adduced to illustrate the potential of the OC format, which enables ease of classification and detailed simulation of energy efficiency for individual vehicles, with application in vehicle design optimization and selection, production planning, and predictive maintenance. In particular, for the track used in the first example, a Volvo FH13 equipped with a diesel engine, simulation results indicate mean CO2 emissions of around 1700 g km-1, with a standard deviation of 360 g km-1; in the second example, dealing with electrical fleet sizing, the optimal proportion shows a predominance of tractor-semitrailer vehicles (70%) equipping 4 motors and 11 battery packs.

sted, utgiver, år, opplag, sider
Institute of Electrical and Electronics Engineers Inc. , 2023. Vol. 11, s. 73268-
Emneord [en]
autoregressive models, Autoregressive processes, Generators, Kinematics, Markov models, Markov processes, mission classification, Operating cycle, Random variables, road transport mission, Roads, Standards, stochastic modeling, Stochastic processes, Surfaces, Diesel engines, Energy efficiency, Fleet operations, Production control, Roads and streets, Stochastic models, Stochastic systems, Vehicles, Auto regressive process, Autoregressive modelling, Generator, Markov modeling, Road, Road transports, Stochastic-modeling, Classification (of information)
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Identifikatorer
URN: urn:nbn:se:ri:diva-65748DOI: 10.1109/ACCESS.2023.3295989Scopus ID: 2-s2.0-85165273811OAI: oai:DiVA.org:ri-65748DiVA, id: diva2:1785987
Tilgjengelig fra: 2023-08-07 Laget: 2023-08-07 Sist oppdatert: 2024-05-27bibliografisk kontrollert

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Godio, MicheleJohannesson, Pär

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