An Optimal Sizing Methodology for Fuel Cell Hybrid Trucks

Asier Alonso Tejeda; Borja Hériz Revuelta; Miguel Allende Marcos; Iban Vicente Makazaga; Pablo Prieto Arce; Joshue Pérez Rastelli

doi:10.1109/ITSC57777.2023.10422454

An Optimal Sizing Methodology for Fuel Cell Hybrid Trucks

Asier Alonso Tejeda
, Borja Hériz Revuelta
, Miguel Allende Marcos
, Iban Vicente Makazaga
, Pablo Prieto Arce
, Joshue Pérez Rastelli

Foundation TECNALIA Research & Innovation

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

4 Citations (Scopus)

Abstract

Fuel Cell Serial Hybrid heavy-duty trucks are expected to progressively replace diesel trucks due to their negative contribution to climate change. This transition entails adapting the actual fleets to new layouts, which requires an accurate sizing of the new components. Hence, in this paper a digital twin of a fuel cell hybrid truck is developed and a route-dependant process for finding the optimal sizing of the battery and the fuel cell is proposed. Three different optimization algorithms (gradient descent, pattern search and simplex search) are described, studied and their results are comprehensively compared.

Original language	English
Title of host publication	2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	298-305
Number of pages	8
ISBN (Electronic)	9798350399462
DOIs	https://doi.org/10.1109/ITSC57777.2023.10422454
Publication status	Published - 2023
Event	26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023 - Bilbao, Spain Duration: 24 Sept 2023 → 28 Sept 2023

Publication series

Name	IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
ISSN (Print)	2153-0009
ISSN (Electronic)	2153-0017

Conference

Conference	26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023
Country/Territory	Spain
City	Bilbao
Period	24/09/23 → 28/09/23

UN SDGs

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

SDG 7 Affordable and Clean Energy

Access to Document

10.1109/ITSC57777.2023.10422454

Cite this

Tejeda, A. A., Revuelta, B. H., Marcos, M. A., Makazaga, I. V., Arce, P. P., & Rastelli, J. P. (2023). An Optimal Sizing Methodology for Fuel Cell Hybrid Trucks. In 2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023 (pp. 298-305). (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITSC57777.2023.10422454

Tejeda, Asier Alonso ; Revuelta, Borja Hériz ; Marcos, Miguel Allende et al. / An Optimal Sizing Methodology for Fuel Cell Hybrid Trucks. 2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 298-305 (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC).

@inproceedings{856ba1d6860948d19592bb916ab33f28,

title = "An Optimal Sizing Methodology for Fuel Cell Hybrid Trucks",

abstract = "Fuel Cell Serial Hybrid heavy-duty trucks are expected to progressively replace diesel trucks due to their negative contribution to climate change. This transition entails adapting the actual fleets to new layouts, which requires an accurate sizing of the new components. Hence, in this paper a digital twin of a fuel cell hybrid truck is developed and a route-dependant process for finding the optimal sizing of the battery and the fuel cell is proposed. Three different optimization algorithms (gradient descent, pattern search and simplex search) are described, studied and their results are comprehensively compared.",

author = "Tejeda, \{Asier Alonso\} and Revuelta, \{Borja H{\'e}riz\} and Marcos, \{Miguel Allende\} and Makazaga, \{Iban Vicente\} and Arce, \{Pablo Prieto\} and Rastelli, \{Joshue P{\'e}rez\}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023 ; Conference date: 24-09-2023 Through 28-09-2023",

year = "2023",

doi = "10.1109/ITSC57777.2023.10422454",

language = "English",

series = "IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC",

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

pages = "298--305",

booktitle = "2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023",

address = "United States",

}

Tejeda, AA, Revuelta, BH, Marcos, MA, Makazaga, IV, Arce, PP & Rastelli, JP 2023, An Optimal Sizing Methodology for Fuel Cell Hybrid Trucks. in 2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023. IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, Institute of Electrical and Electronics Engineers Inc., pp. 298-305, 26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023, Bilbao, Spain, 24/09/23. https://doi.org/10.1109/ITSC57777.2023.10422454

An Optimal Sizing Methodology for Fuel Cell Hybrid Trucks. / Tejeda, Asier Alonso; Revuelta, Borja Hériz; Marcos, Miguel Allende et al.
2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 298-305 (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC).

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

TY - GEN

T1 - An Optimal Sizing Methodology for Fuel Cell Hybrid Trucks

AU - Tejeda, Asier Alonso

AU - Revuelta, Borja Hériz

AU - Marcos, Miguel Allende

AU - Makazaga, Iban Vicente

AU - Arce, Pablo Prieto

AU - Rastelli, Joshue Pérez

PY - 2023

Y1 - 2023

N2 - Fuel Cell Serial Hybrid heavy-duty trucks are expected to progressively replace diesel trucks due to their negative contribution to climate change. This transition entails adapting the actual fleets to new layouts, which requires an accurate sizing of the new components. Hence, in this paper a digital twin of a fuel cell hybrid truck is developed and a route-dependant process for finding the optimal sizing of the battery and the fuel cell is proposed. Three different optimization algorithms (gradient descent, pattern search and simplex search) are described, studied and their results are comprehensively compared.

AB - Fuel Cell Serial Hybrid heavy-duty trucks are expected to progressively replace diesel trucks due to their negative contribution to climate change. This transition entails adapting the actual fleets to new layouts, which requires an accurate sizing of the new components. Hence, in this paper a digital twin of a fuel cell hybrid truck is developed and a route-dependant process for finding the optimal sizing of the battery and the fuel cell is proposed. Three different optimization algorithms (gradient descent, pattern search and simplex search) are described, studied and their results are comprehensively compared.

UR - https://www.scopus.com/pages/publications/85186499155

U2 - 10.1109/ITSC57777.2023.10422454

DO - 10.1109/ITSC57777.2023.10422454

M3 - Conference contribution

AN - SCOPUS:85186499155

T3 - IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC

SP - 298

EP - 305

BT - 2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023

Y2 - 24 September 2023 through 28 September 2023

ER -

Tejeda AA, Revuelta BH, Marcos MA, Makazaga IV, Arce PP, Rastelli JP. An Optimal Sizing Methodology for Fuel Cell Hybrid Trucks. In 2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 298-305. (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC). doi: 10.1109/ITSC57777.2023.10422454

An Optimal Sizing Methodology for Fuel Cell Hybrid Trucks

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UN SDGs

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