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Heavy haul digital twin – Proof of concept for 8-axle high adhesion 10 MWh battery electric locomotive

Digital twin analysis can be used to ensure that locomotive design development satisfies railway standards, guidelines, codes of practice and operational needs in terms of practical applications for achieving net-zero-emission goals in locomotive traction. Recent digital twin research studies in this area, performed at the Centre for Railway Engineering located at CQUniversity, show that the implementation of 6-axle 5MWh battery electric locomotives in heavy haul operations for these purposes can be problematic due to the existing limitations for sizing and optimizing zero carbon energy storage options and train operational scenarios. The introduction of a digital twin in the locomotive design process allows performing a comprehensive assessment of design requirements and made it possible to resolve these sizing and optimizing tasks with the implementation of 8-axle locomotives. This paper presents a concept that incorporates advancements in the modelling techniques for an investigation of a proposed design of a high adhesion 10 MWh battery electric locomotive (HABEL) at the proof of concept design stage using digital twin techniques. The multidisciplinary approach built on the V-model approach widely used in systems engineering is discussed and the proof-of-concept implementation is presented.

History

Editor

Gräbe PJ; Merheb A; Hume P; Mol C

Start Page

1125

End Page

1129

Number of Pages

5

Start Date

2023-08-27

Finish Date

2023-08-31

ISBN-13

9780796123428

Location

Rio De Janeiro, Brazil

Publisher

International Heavy Haul Association (IHHA)

Place of Publication

Virginia Beach, VA

Peer Reviewed

  • Yes

Open Access

  • No

Author Research Institute

  • Centre for Railway Engineering

Era Eligible

  • Yes

Name of Conference

12th International Heavy Haul Association Conference 2023 (IHHA Rio 2023)

Parent Title

Proceedings of the 12th International Heavy Haul Association Conference 2023 (IHHA Rio 2023)