Design of an Energy Management-Based Model Predictive Control for Catenary-Free Hybrid Trains

This paper proposes an energy management system based on model predictive control (MPC) for catenary-free hybrid trains powered by supercapacitors and lithium-ion batteries. Spurred by South Africa’s railway case study, where the catenary-free scenario is common due to the lack of cabled tracks in several areas, the proposed MPC has the capability of enhancing efficiency and reliability while optimizing power distribution. Simulation results and a comparative analysis with respect to the train currently operating on the same route and a heuristic-based approach demonstrate significant cost savings in both operational and building expenses. Additionally, energy losses are reduced, further improving the overall performance.

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Publication Details

Journal
IFAC-PapersOnLine
Published
2025-01-01
DOI
https://doi.org/10.1016/j.ifacol.2025.08.153
Primary Topic
Electric and Hybrid Vehicle Technologies
Type
article
Field-Weighted Citation Impact
0.00
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article

Design of an Energy Management-Based Model Predictive Control for Catenary-Free Hybrid Trains

Edward Boje, Alessio La Bella, Gian Paolo Incremona, Patrizio Colaneri et al.
IFAC-PapersOnLine
Electric and Hybrid Vehicle Technologies
article

Design of an Energy Management-Based Model Predictive Control for Catenary-Free Hybrid Trains

Edward Boje, Alessio La Bella, Gian Paolo Incremona, Patrizio Colaneri, Manuel Camarda
article en

Abstract

This paper proposes an energy management system based on model predictive control (MPC) for catenary-free hybrid trains powered by supercapacitors and lithium-ion batteries. Spurred by South Africa’s railway case study, where the catenary-free scenario is common due to the lack of cabled tracks in several areas, the proposed MPC has the capability of enhancing efficiency and reliability while optimizing power distribution. Simulation results and a comparative analysis with respect to the train currently operating on the same route and a heuristic-based approach demonstrate significant cost savings in both operational and building expenses. Additionally, energy losses are reduced, further improving the overall performance.

IFAC-PapersOnLineVol. 59(9)
University of Cape Town (ZA), Politecnico di Milano (IT)
Openalex Percentile: Top 72%
Electric and Hybrid Vehicle Technologies
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Design of an Energy Management-Based Model Predictive Control for Catenary-Free Hybrid Trains — Edward Boje, Alessio La Bella, et al. · IFAC-PapersOnLine (2025) | TGRS Research Map | TGRS