Optimization of electric vehicle system utilizing a hybrid particle swarm algorithm

Mikaela Ranta; Mikko Pihlatie; Ari Hentunen

Optimization of electric vehicle system utilizing a hybrid particle swarm algorithm

Mikaela Ranta (Corresponding author), Mikko Pihlatie, Ari Hentunen

BA2C04 Electrical powertrains and storage

Research output: Chapter in Book/Report/Conference proceeding › Conference abstract in proceedings › Scientific

Abstract

A method for optimization of electric vehicle fleets is proposed. The method utilizes a hybrid particle swarm optimization algorithm with both continuous and binary variables. The battery capacity, battery chemistry, charging locations, charging power and number of chargers are obtained as an output of the optimization. A vehicle fleet simulation model is used to evaluate the cost of the system. The energy consumption for various routes and the costs for charging infrastructure, energy and purchase of vehicles are obtained as a result from the simulations. The battery ageing is evaluated based on the state-of-charge cycles. The method is demonstrated on two different cases of electric buses in the Helsinki region.

Original language	English
Title of host publication	Proceedings of TRA2020, the 8th Transport Research Arena
Subtitle of host publication	Rethinking transport – towards clean and inclusive mobility
Publisher	Liikenne- ja viestintävirasto Traficom
Pages	164
Number of pages	1
ISBN (Electronic)	978-952-311-484-5
Publication status	Published - 2019
Event	8th Transport Research Arena, TRA 2020 - Conference cancelled - Helsinki, Finland Duration: 27 Apr 2020 → 30 Apr 2020 https://traconference.eu/overview/

Publication series

Series	Traficom Research Reports
Number	7/2020
ISSN	2660-8781

Conference

Conference	8th Transport Research Arena, TRA 2020 - Conference cancelled
Abbreviated title	TRA 2020
Country	Finland
City	Helsinki
Period	27/04/20 → 30/04/20
Internet address	https://traconference.eu/overview/

Access to Document

https://www.traficom.fi/sites/default/files/media/publication/TRA2020-Book-of-Abstract-Traficom-research-publication.pdf

Fingerprint Dive into the research topics of 'Optimization of electric vehicle system utilizing a hybrid particle swarm algorithm'. Together they form a unique fingerprint.

Cite this

Ranta, M., Pihlatie, M., & Hentunen, A. (2019). Optimization of electric vehicle system utilizing a hybrid particle swarm algorithm. In Proceedings of TRA2020, the 8th Transport Research Arena: Rethinking transport – towards clean and inclusive mobility (pp. 164). Liikenne- ja viestintävirasto Traficom. Traficom Research Reports, No. 7/2020 https://www.traficom.fi/sites/default/files/media/publication/TRA2020-Book-of-Abstract-Traficom-research-publication.pdf

@inbook{c42e0faef2da49a882dcf0f800a5d086,

title = "Optimization of electric vehicle system utilizing a hybrid particle swarm algorithm",

abstract = "A method for optimization of electric vehicle fleets is proposed. The method utilizes a hybrid particle swarm optimization algorithm with both continuous and binary variables. The battery capacity, battery chemistry, charging locations, charging power and number of chargers are obtained as an output of the optimization. A vehicle fleet simulation model is used to evaluate the cost of the system. The energy consumption for various routes and the costs for charging infrastructure, energy and purchase of vehicles are obtained as a result from the simulations. The battery ageing is evaluated based on the state-of-charge cycles. The method is demonstrated on two different cases of electric buses in the Helsinki region.",

author = "Mikaela Ranta and Mikko Pihlatie and Ari Hentunen",

note = "No proceedings? Two journals are publishing special issues from the conference: European Transport Research Review and Utilities Policy.; 8th Transport Research Arena, TRA 2020 - Conference cancelled, TRA 2020 ; Conference date: 27-04-2020 Through 30-04-2020",

year = "2019",

language = "English",

series = "Traficom Research Reports",

publisher = "Liikenne- ja viestint{\"a}virasto Traficom",

number = "7/2020",

pages = "164",

booktitle = "Proceedings of TRA2020, the 8th Transport Research Arena",

address = "Finland",

url = "https://traconference.eu/overview/",

}

Ranta, M , Pihlatie, M & Hentunen, A 2019, Optimization of electric vehicle system utilizing a hybrid particle swarm algorithm. in Proceedings of TRA2020, the 8th Transport Research Arena: Rethinking transport – towards clean and inclusive mobility. Liikenne- ja viestintävirasto Traficom, Traficom Research Reports, no. 7/2020, pp. 164, 8th Transport Research Arena, TRA 2020 - Conference cancelled, Helsinki, Finland, 27/04/20. <https://www.traficom.fi/sites/default/files/media/publication/TRA2020-Book-of-Abstract-Traficom-research-publication.pdf>

Optimization of electric vehicle system utilizing a hybrid particle swarm algorithm. / Ranta, Mikaela (Corresponding author); Pihlatie, Mikko ; Hentunen, Ari.

Proceedings of TRA2020, the 8th Transport Research Arena: Rethinking transport – towards clean and inclusive mobility. Liikenne- ja viestintävirasto Traficom, 2019. p. 164 (Traficom Research Reports; No. 7/2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference abstract in proceedings › Scientific

TY - CHAP

T1 - Optimization of electric vehicle system utilizing a hybrid particle swarm algorithm

AU - Ranta, Mikaela

AU - Pihlatie, Mikko

AU - Hentunen, Ari

N1 - No proceedings? Two journals are publishing special issues from the conference: European Transport Research Review and Utilities Policy.

PY - 2019

Y1 - 2019

N2 - A method for optimization of electric vehicle fleets is proposed. The method utilizes a hybrid particle swarm optimization algorithm with both continuous and binary variables. The battery capacity, battery chemistry, charging locations, charging power and number of chargers are obtained as an output of the optimization. A vehicle fleet simulation model is used to evaluate the cost of the system. The energy consumption for various routes and the costs for charging infrastructure, energy and purchase of vehicles are obtained as a result from the simulations. The battery ageing is evaluated based on the state-of-charge cycles. The method is demonstrated on two different cases of electric buses in the Helsinki region.

AB - A method for optimization of electric vehicle fleets is proposed. The method utilizes a hybrid particle swarm optimization algorithm with both continuous and binary variables. The battery capacity, battery chemistry, charging locations, charging power and number of chargers are obtained as an output of the optimization. A vehicle fleet simulation model is used to evaluate the cost of the system. The energy consumption for various routes and the costs for charging infrastructure, energy and purchase of vehicles are obtained as a result from the simulations. The battery ageing is evaluated based on the state-of-charge cycles. The method is demonstrated on two different cases of electric buses in the Helsinki region.

M3 - Conference abstract in proceedings

T3 - Traficom Research Reports

SP - 164

BT - Proceedings of TRA2020, the 8th Transport Research Arena

PB - Liikenne- ja viestintävirasto Traficom

T2 - 8th Transport Research Arena, TRA 2020 - Conference cancelled

Y2 - 27 April 2020 through 30 April 2020

ER -