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Impacts of vehicle fleet electrification in Sweden-a simulation-based assessment of long-distance trips

Bischoff, Joschka LU ; Marquez-Fernandez, Francisco J. LU orcid ; Domingues-Olavarria, Gabriel LU ; Maciejewski, Michal and Nagel, Kai (2019) 6th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2019 In MT-ITS 2019 - 6th International Conference on Models and Technologies for Intelligent Transportation Systems
Abstract

Electrifying road transport is seen as one of the key components in decreasing the carbon footprint of the society as a whole. Recent developments in electric drivetrain and battery technology have helped to design vehicles with ranges that make them independent of public charging infrastructure during most sub-urban and commuting trips. Once long-haul trips are planned, however, these vehicles require a dense network of charging infrastructure. In this paper, the impact of a large-scale electrification of vehicles in long-distance trips is evaluated by combining an agent-based long distance transport model of Sweden with a detailed model of energy consumption and battery charging. Energy consumption and charging schemes are simulated... (More)

Electrifying road transport is seen as one of the key components in decreasing the carbon footprint of the society as a whole. Recent developments in electric drivetrain and battery technology have helped to design vehicles with ranges that make them independent of public charging infrastructure during most sub-urban and commuting trips. Once long-haul trips are planned, however, these vehicles require a dense network of charging infrastructure. In this paper, the impact of a large-scale electrification of vehicles in long-distance trips is evaluated by combining an agent-based long distance transport model of Sweden with a detailed model of energy consumption and battery charging. Energy consumption and charging schemes are simulated for different types of vehicles and chargers. In a first application, all vehicle traffic is electrified. Results demonstrate that the daily estimate for energy consumption is in the region of 150 GWh. This equals roughly 40% of the current Swedish electricity consumption. Energy consumption is the highest along in the motorway network connecting the south of the country (Malmö, Göteborg and Stockholm). Along these motorways, also the highest demand for charging infrastructure arises. Nationwide, two peak times for vehicle charging seem to exist: One is around lunch time and another in the mid-Afternoon. During the first peak, overall energy demand is presumably the highest.

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Please use this url to cite or link to this publication:
author
; ; ; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Electric Vehicles, long distance travel, MATSim, Sweden, Transport Simulation
host publication
MT-ITS 2019 - 6th International Conference on Models and Technologies for Intelligent Transportation Systems
series title
MT-ITS 2019 - 6th International Conference on Models and Technologies for Intelligent Transportation Systems
article number
8883384
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
6th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2019
conference location
Krakow, Poland
conference dates
2019-06-05 - 2019-06-07
external identifiers
  • scopus:85071293126
ISBN
9781538694848
DOI
10.1109/MTITS.2019.8883384
language
English
LU publication?
yes
additional info
Publisher Copyright: © 2019 IEEE.
id
06a6ced5-2f73-4879-a8d2-0e52b8a05dc2
date added to LUP
2024-09-29 17:55:15
date last changed
2024-10-01 11:33:31
@inproceedings{06a6ced5-2f73-4879-a8d2-0e52b8a05dc2,
  abstract     = {{<p>Electrifying road transport is seen as one of the key components in decreasing the carbon footprint of the society as a whole. Recent developments in electric drivetrain and battery technology have helped to design vehicles with ranges that make them independent of public charging infrastructure during most sub-urban and commuting trips. Once long-haul trips are planned, however, these vehicles require a dense network of charging infrastructure. In this paper, the impact of a large-scale electrification of vehicles in long-distance trips is evaluated by combining an agent-based long distance transport model of Sweden with a detailed model of energy consumption and battery charging. Energy consumption and charging schemes are simulated for different types of vehicles and chargers. In a first application, all vehicle traffic is electrified. Results demonstrate that the daily estimate for energy consumption is in the region of 150 GWh. This equals roughly 40% of the current Swedish electricity consumption. Energy consumption is the highest along in the motorway network connecting the south of the country (Malmö, Göteborg and Stockholm). Along these motorways, also the highest demand for charging infrastructure arises. Nationwide, two peak times for vehicle charging seem to exist: One is around lunch time and another in the mid-Afternoon. During the first peak, overall energy demand is presumably the highest.</p>}},
  author       = {{Bischoff, Joschka and Marquez-Fernandez, Francisco J. and Domingues-Olavarria, Gabriel and Maciejewski, Michal and Nagel, Kai}},
  booktitle    = {{MT-ITS 2019 - 6th International Conference on Models and Technologies for Intelligent Transportation Systems}},
  isbn         = {{9781538694848}},
  keywords     = {{Electric Vehicles; long distance travel; MATSim; Sweden; Transport Simulation}},
  language     = {{eng}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  series       = {{MT-ITS 2019 - 6th International Conference on Models and Technologies for Intelligent Transportation Systems}},
  title        = {{Impacts of vehicle fleet electrification in Sweden-a simulation-based assessment of long-distance trips}},
  url          = {{http://dx.doi.org/10.1109/MTITS.2019.8883384}},
  doi          = {{10.1109/MTITS.2019.8883384}},
  year         = {{2019}},
}