On-line Test of a Real-Time Velocity Prediction for E-bus Energy Consumption Estimation

Camiel J.J. Beckers; Igo J.M. Besselink; Henk Nijmeijer

doi:10.1109/VPPC53923.2021.9699205

On-line Test of a Real-Time Velocity Prediction for E-bus Energy Consumption Estimation

Camiel J.J. Beckers
, Igo J.M. Besselink
, Henk Nijmeijer

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

5 Citations (Scopus)

263 Downloads (Pure)

Abstract

To facilitate dynamic vehicle scheduling for battery electric city buses, a real-time on-line energy consumption prediction model is proposed. The model utilizes the current vehicle velocity and position, combined with knowledge of the remaining route, to predict the total trip energy. The model consists of a remaining velocity profile predictor and a longitudinal dynamics model. The algorithm is demonstrated in a Hardware-in-the-Loop experiment with a battery electric bus. The model has an average error of 3.1% with respect to the total trip energy and adapts in real-time to unexpected acceleration and deceleration events.

Original language	English
Title of host publication	2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS
Publisher	Institute of Electrical and Electronics Engineers
Number of pages	5
ISBN (Electronic)	9781665405287
DOIs	https://doi.org/10.1109/VPPC53923.2021.9699205
Publication status	Published - 10 Feb 2022
Event	18th IEEE Vehicle Propulsion and Power Conference (VPPC 2021) - Gijon, Spain Duration: 25 Oct 2021 → 28 Oct 2021 Conference number: 18 https://vtsociety.org/events/ieee-vppc-2021/

Conference

Conference	18th IEEE Vehicle Propulsion and Power Conference (VPPC 2021)
Abbreviated title	VPPC 2021
Country/Territory	Spain
City	Gijon
Period	25/10/21 → 28/10/21
Internet address	https://vtsociety.org/events/ieee-vppc-2021/

Funding

This project has received funding from the European Unions Horizon 2020 research and innovation programme under grant agreement No. 713771.

Funders	Funder number
European Union's Horizon 2020 - Research and Innovation Framework Programme	713771

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Electric Vehicle
Battery Electric Bus
Energy Consumption
Prediction
Hardward-in-the-Loop
Hardware-in-the-Loop (HiL)

Access to Document

10.1109/VPPC53923.2021.9699205Licence: Unspecified

VPPC21_Post-Print_BeckersBesselinkNijmeijer_2021-09-06Final author version , 871 KB

Cite this

@inproceedings{60a47e1ac2794613b046b950504747e8,

title = "On-line Test of a Real-Time Velocity Prediction for E-bus Energy Consumption Estimation",

abstract = "To facilitate dynamic vehicle scheduling for battery electric city buses, a real-time on-line energy consumption prediction model is proposed. The model utilizes the current vehicle velocity and position, combined with knowledge of the remaining route, to predict the total trip energy. The model consists of a remaining velocity profile predictor and a longitudinal dynamics model. The algorithm is demonstrated in a Hardware-in-the-Loop experiment with a battery electric bus. The model has an average error of 3.1\% with respect to the total trip energy and adapts in real-time to unexpected acceleration and deceleration events.",

keywords = "Electric Vehicle, Battery Electric Bus, Energy Consumption, Prediction, Hardward-in-the-Loop, Hardware-in-the-Loop (HiL)",

author = "Beckers, \{Camiel J.J.\} and Besselink, \{Igo J.M.\} and Henk Nijmeijer",

year = "2022",

month = feb,

day = "10",

doi = "10.1109/VPPC53923.2021.9699205",

language = "English",

booktitle = "2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

note = "18th IEEE Vehicle Propulsion and Power Conference (VPPC 2021), VPPC 2021 ; Conference date: 25-10-2021 Through 28-10-2021",

url = "https://vtsociety.org/events/ieee-vppc-2021/",

}

Beckers, CJJ, Besselink, IJM & Nijmeijer, H 2022, On-line Test of a Real-Time Velocity Prediction for E-bus Energy Consumption Estimation. in 2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS., 9699205, Institute of Electrical and Electronics Engineers, 18th IEEE Vehicle Propulsion and Power Conference (VPPC 2021), Gijon, Spain, 25/10/21. https://doi.org/10.1109/VPPC53923.2021.9699205

On-line Test of a Real-Time Velocity Prediction for E-bus Energy Consumption Estimation. / Beckers, Camiel J.J.; Besselink, Igo J.M.; Nijmeijer, Henk.
2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS. Institute of Electrical and Electronics Engineers, 2022. 9699205.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - On-line Test of a Real-Time Velocity Prediction for E-bus Energy Consumption Estimation

AU - Beckers, Camiel J.J.

AU - Besselink, Igo J.M.

AU - Nijmeijer, Henk

N1 - Conference code: 18

PY - 2022/2/10

Y1 - 2022/2/10

N2 - To facilitate dynamic vehicle scheduling for battery electric city buses, a real-time on-line energy consumption prediction model is proposed. The model utilizes the current vehicle velocity and position, combined with knowledge of the remaining route, to predict the total trip energy. The model consists of a remaining velocity profile predictor and a longitudinal dynamics model. The algorithm is demonstrated in a Hardware-in-the-Loop experiment with a battery electric bus. The model has an average error of 3.1% with respect to the total trip energy and adapts in real-time to unexpected acceleration and deceleration events.

AB - To facilitate dynamic vehicle scheduling for battery electric city buses, a real-time on-line energy consumption prediction model is proposed. The model utilizes the current vehicle velocity and position, combined with knowledge of the remaining route, to predict the total trip energy. The model consists of a remaining velocity profile predictor and a longitudinal dynamics model. The algorithm is demonstrated in a Hardware-in-the-Loop experiment with a battery electric bus. The model has an average error of 3.1% with respect to the total trip energy and adapts in real-time to unexpected acceleration and deceleration events.

KW - Electric Vehicle

KW - Battery Electric Bus

KW - Energy Consumption

KW - Prediction

KW - Hardward-in-the-Loop

KW - Hardware-in-the-Loop (HiL)

UR - https://www.scopus.com/pages/publications/85126233256

U2 - 10.1109/VPPC53923.2021.9699205

DO - 10.1109/VPPC53923.2021.9699205

M3 - Conference contribution

BT - 2021 IEEE Vehicle Power and Propulsion Conference, VPPC 2021 - ProceedingS

PB - Institute of Electrical and Electronics Engineers

T2 - 18th IEEE Vehicle Propulsion and Power Conference (VPPC 2021)

Y2 - 25 October 2021 through 28 October 2021

ER -

On-line Test of a Real-Time Velocity Prediction for E-bus Energy Consumption Estimation

Abstract

Conference

Funding

UN SDGs

Keywords

Access to Document

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Cite this