Intelligent and adaptive fleet energy management strategy for hybrid electric buses

Jon Ander Lopez-Ibarra; Nerea Goitia-Zabaleta; Haritza Camblong; Aitor Milo; Haizea Gaztanaga

doi:10.1109/VPPC46532.2019.8952368

Intelligent and adaptive fleet energy management strategy for hybrid electric buses

Jon Ander Lopez-Ibarra
, Nerea Goitia-Zabaleta
, Haritza Camblong
, Aitor Milo
, Haizea Gaztanaga

IKERLAN

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

4 Citations (Scopus)

Abstract

Learning based energy management strategies are promising methods, due to the high adaptability and the capability to learn from historical data. Widening the scope to a whole fleet, allows to learn from a more extend data-base and wider range of operating conditions. This paper aims to develop a methodology for improving the overall energetic efficiency of a fleet. In this regard, the main contribution lyes on the development of an intelligent decision maker, with the goal to design improved and adapted energy management strategies for each bus operating on a predefined route. The intelligent decision maker is driven by an adaptive neuro-fuzzy inference system technique that learns from the optimal operation optimized with dynamic programming. The obtained results in the developed EMS have shown similarities with the dynamic programming operation, reaching close fuel consumptions, 0.01% of difference and improvements up to 16% of fuel consumption against the initial EMS.

Original language	English
Title of host publication	2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728112497
DOIs	https://doi.org/10.1109/VPPC46532.2019.8952368
Publication status	Published - Oct 2019
Externally published	Yes
Event	2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Hanoi, Viet Nam Duration: 14 Oct 2019 → 17 Oct 2019

Publication series

Name	2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings

Conference

Conference	2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019
Country/Territory	Viet Nam
City	Hanoi
Period	14/10/19 → 17/10/19

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Dynamic programming
Fleet energy management
Hybrid electric bus
Intelligent decision maker
Neuro-fuzzy

Access to Document

10.1109/VPPC46532.2019.8952368

Cite this

Lopez-Ibarra, J. A., Goitia-Zabaleta, N., Camblong, H., Milo, A., & Gaztanaga, H. (2019). Intelligent and adaptive fleet energy management strategy for hybrid electric buses. In 2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings Article 8952368 (2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VPPC46532.2019.8952368

Lopez-Ibarra, Jon Ander ; Goitia-Zabaleta, Nerea ; Camblong, Haritza et al. / Intelligent and adaptive fleet energy management strategy for hybrid electric buses. 2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings).

@inproceedings{9622b849a58247b7946ab121bddd8607,

title = "Intelligent and adaptive fleet energy management strategy for hybrid electric buses",

abstract = "Learning based energy management strategies are promising methods, due to the high adaptability and the capability to learn from historical data. Widening the scope to a whole fleet, allows to learn from a more extend data-base and wider range of operating conditions. This paper aims to develop a methodology for improving the overall energetic efficiency of a fleet. In this regard, the main contribution lyes on the development of an intelligent decision maker, with the goal to design improved and adapted energy management strategies for each bus operating on a predefined route. The intelligent decision maker is driven by an adaptive neuro-fuzzy inference system technique that learns from the optimal operation optimized with dynamic programming. The obtained results in the developed EMS have shown similarities with the dynamic programming operation, reaching close fuel consumptions, 0.01\% of difference and improvements up to 16\% of fuel consumption against the initial EMS.",

keywords = "Dynamic programming, Fleet energy management, Hybrid electric bus, Intelligent decision maker, Neuro-fuzzy",

author = "Lopez-Ibarra, \{Jon Ander\} and Nerea Goitia-Zabaleta and Haritza Camblong and Aitor Milo and Haizea Gaztanaga",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 ; Conference date: 14-10-2019 Through 17-10-2019",

year = "2019",

month = oct,

doi = "10.1109/VPPC46532.2019.8952368",

language = "English",

series = "2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings",

address = "United States",

}

Lopez-Ibarra, JA, Goitia-Zabaleta, N, Camblong, H, Milo, A & Gaztanaga, H 2019, Intelligent and adaptive fleet energy management strategy for hybrid electric buses. in 2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings., 8952368, 2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019, Hanoi, Viet Nam, 14/10/19. https://doi.org/10.1109/VPPC46532.2019.8952368

Intelligent and adaptive fleet energy management strategy for hybrid electric buses. / Lopez-Ibarra, Jon Ander; Goitia-Zabaleta, Nerea; Camblong, Haritza et al.
2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. 8952368 (2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings).

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

TY - GEN

T1 - Intelligent and adaptive fleet energy management strategy for hybrid electric buses

AU - Lopez-Ibarra, Jon Ander

AU - Goitia-Zabaleta, Nerea

AU - Camblong, Haritza

AU - Milo, Aitor

AU - Gaztanaga, Haizea

PY - 2019/10

Y1 - 2019/10

N2 - Learning based energy management strategies are promising methods, due to the high adaptability and the capability to learn from historical data. Widening the scope to a whole fleet, allows to learn from a more extend data-base and wider range of operating conditions. This paper aims to develop a methodology for improving the overall energetic efficiency of a fleet. In this regard, the main contribution lyes on the development of an intelligent decision maker, with the goal to design improved and adapted energy management strategies for each bus operating on a predefined route. The intelligent decision maker is driven by an adaptive neuro-fuzzy inference system technique that learns from the optimal operation optimized with dynamic programming. The obtained results in the developed EMS have shown similarities with the dynamic programming operation, reaching close fuel consumptions, 0.01% of difference and improvements up to 16% of fuel consumption against the initial EMS.

AB - Learning based energy management strategies are promising methods, due to the high adaptability and the capability to learn from historical data. Widening the scope to a whole fleet, allows to learn from a more extend data-base and wider range of operating conditions. This paper aims to develop a methodology for improving the overall energetic efficiency of a fleet. In this regard, the main contribution lyes on the development of an intelligent decision maker, with the goal to design improved and adapted energy management strategies for each bus operating on a predefined route. The intelligent decision maker is driven by an adaptive neuro-fuzzy inference system technique that learns from the optimal operation optimized with dynamic programming. The obtained results in the developed EMS have shown similarities with the dynamic programming operation, reaching close fuel consumptions, 0.01% of difference and improvements up to 16% of fuel consumption against the initial EMS.

KW - Dynamic programming

KW - Fleet energy management

KW - Hybrid electric bus

KW - Intelligent decision maker

KW - Neuro-fuzzy

UR - https://www.scopus.com/pages/publications/85078748636

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DO - 10.1109/VPPC46532.2019.8952368

M3 - Conference contribution

AN - SCOPUS:85078748636

T3 - 2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings

BT - 2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019

Y2 - 14 October 2019 through 17 October 2019

ER -

Lopez-Ibarra JA, Goitia-Zabaleta N, Camblong H, Milo A, Gaztanaga H. Intelligent and adaptive fleet energy management strategy for hybrid electric buses. In 2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. 8952368. (2019 IEEE Vehicle Power and Propulsion Conference, VPPC 2019 - Proceedings). doi: 10.1109/VPPC46532.2019.8952368

Intelligent and adaptive fleet energy management strategy for hybrid electric buses

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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