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Heterogeneous Models Based Distributed Predictive Control for Heavy-haul Trains
ID：21 View Protection：ATTENDEE Updated Time：2023-11-20 13:45:33 Hits：949 Oral Presentation

Start Time：2023-12-09 14:15（Asia/Shanghai）

Duration：15min

Session：S5 Traction power supply technology and application » S5Traction power supply technology and application

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Abstract
In order to further improve the line capacity and locomotive fleet safety operation for busy heavy-haul railways, a heterogeneous group modeling approach is adopted in this paper to identify locomotive fleets with different dynamic characteristics. By analyzing adjacent coupling characteristics between different locomotive fleets, a topology graph with stable interconnection parameters for heterogeneous groups is derived. To ensure the smooth operation of heavy-haul train groups and prevent significant speed control errors during operation, a distributed dynamic matrix predictive control algorithm has been developed. Joint simulations based on heterogeneous groups such as AC electric locomotive HXD3, DC electric locomotive SS4B, and diesel locomotive HXN3 demonstrate that this approach provides reference for stable coupling of different types of overloaded locomotives, reduces driver workload, and achieves safe and smooth operation.
 
Keywords
Distributed predictive control; Dynamic matrix control; Heavy-haul trains; Heterogeneous groups; Stable topology graph.
Speaker
Zhang Kunpeng
Lecturer East China Jiaotong University

Submission Author
Zhang Kunpeng East China Jiaotong University
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Important Date

  • Conference Date

    Dec 08

    2023

    to

    Dec 10

    2023

  • Nov 01 2023

    Draft paper submission deadline

  • Dec 10 2023

    Registration deadline

Sponsored By
IEEE IAS
Organized By
Southwest Jiaotong University (SWJTU)
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