This thesis addresses the energy management control problem for railway systems in the case of hybrid trains, a promising innovation for sustainable transportation, focusing on a train equipped with lithium-ion batteries and hydrogen fuel cells, also enhanced by regenerative braking capabilities. This hybrid train can operate both connected to the catenary system and in catenary-free scenarios, providing a versatile solution for various railway environments. The main contributions of this thesis include the development of a detailed electrical model of the train, the design of an advanced control strategy based on model predictive control (MPC), and a comparative analysis with existing approaches. Initially, a precise electrical circuit model is introduced, deeply analyzing all components such as power converters, batteries and fuel cells. The representation captures transient behaviors, ensuring an accurate reflection of the train’s real-world operations. This model is then simplified for control purposes, enhancing computational efficiency while maintaining accuracy, as the results remain consistent with the original representation. A MPC strategy with an economic cost is then designed, focusing on optimizing energy management and minimizing power losses, also ensuring that the batteries’ state of charge and the hydrogen levels in the fuel cells remain within their optimal operating ranges, enhancing both performance and system longevity. The thesis, relying on real data provided by the industrial partner Alstom, concludes with a comparative analysis, evaluating the proposed control strategy against two alternatives: a MPC for a train powered solely by batteries and a heuristic control approach. This comparison demonstrates the superiority of the adopted strategy in terms of efficiency and reliability. A robustness analysis and a scenario with multiple catenary-free sections further validate the approach, highlighting its effectiveness in demanding situations where power demands are considerably increased and in areas with limited electrification infrastructure.
Questo lavoro di tesi affronta il problema della gestione energetica nei sistemi su rotaia nel caso dei treni ibridi, una promettente innovazione per il trasporto sostenibile, e si concentra su un treno dotato di batterie agli ioni di litio e celle a combustibile a idrogeno, sfruttando anche la frenata rigenerativa. Tale treno può operare sia connesso alla rete elettrica sia in scenari senza catenaria, offrendo una soluzione versatile in diversi casi. I principali contributi di questa tesi includono lo sviluppo di un modello elettrico dettagliato del treno, la progettazione di una strategia di controllo avanzata basata sul controllo predittivo (MPC) e un'analisi comparativa con approcci esistenti. Inizialmente, viene creato un modello preciso del circuito elettrico, analizzando in dettaglio tutti i componenti, come i convertitori di potenza, le batterie e le celle a combustibile. Tale rappresentazione cattura i transitori, garantendo una proiezione accurata del funzionamento reale del treno. Questo modello viene poi semplificato per la sintesi del controllore, migliorandone l'efficienza computazionale senza sacrificare la precisione, come evidenziato dai risultati coerenti con la rappresentazione originale. Un controllore di tipo predittivo (MPC) con un costo di tipo economico viene quindi progettato, concentrandosi sull'ottimizzazione della gestione energetica e minimizzazione delle perdite, garantendo inoltre che lo stato di carica delle batterie e i livelli di idrogeno rimangano entro i loro intervalli operativi ottimali, migliorando sia le prestazioni sia la longevità del sistema. La tesi, sulla base di dati reali forniti dal partner industriale Alstom, si conclude con un'analisi comparativa, valutando la strategia di controllo proposta rispetto a due alternative: un MPC per un treno alimentato esclusivamente da batterie e un approccio di controllo euristico. Questo confronto dimostra la superiorità della strategia proposta in termini di efficienza e affidabilità. Un'analisi di robustezza e uno scenario con più tratti senza catenaria validano ulteriormente l'approccio, evidenziandone l'efficacia in situazioni critiche e in aree con infrastrutture limitate.
Model Predictive Control for Energy Saving of Hybrid Trains in Catenary-Free Scenarios
Camarda, Manuel
2023/2024
Abstract
This thesis addresses the energy management control problem for railway systems in the case of hybrid trains, a promising innovation for sustainable transportation, focusing on a train equipped with lithium-ion batteries and hydrogen fuel cells, also enhanced by regenerative braking capabilities. This hybrid train can operate both connected to the catenary system and in catenary-free scenarios, providing a versatile solution for various railway environments. The main contributions of this thesis include the development of a detailed electrical model of the train, the design of an advanced control strategy based on model predictive control (MPC), and a comparative analysis with existing approaches. Initially, a precise electrical circuit model is introduced, deeply analyzing all components such as power converters, batteries and fuel cells. The representation captures transient behaviors, ensuring an accurate reflection of the train’s real-world operations. This model is then simplified for control purposes, enhancing computational efficiency while maintaining accuracy, as the results remain consistent with the original representation. A MPC strategy with an economic cost is then designed, focusing on optimizing energy management and minimizing power losses, also ensuring that the batteries’ state of charge and the hydrogen levels in the fuel cells remain within their optimal operating ranges, enhancing both performance and system longevity. The thesis, relying on real data provided by the industrial partner Alstom, concludes with a comparative analysis, evaluating the proposed control strategy against two alternatives: a MPC for a train powered solely by batteries and a heuristic control approach. This comparison demonstrates the superiority of the adopted strategy in terms of efficiency and reliability. A robustness analysis and a scenario with multiple catenary-free sections further validate the approach, highlighting its effectiveness in demanding situations where power demands are considerably increased and in areas with limited electrification infrastructure.File | Dimensione | Formato | |
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2024_10_Camarda_Executive_Summary.pdf
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2024_10_Camarda_Tesi.pdf
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Descrizione: Tesi
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https://hdl.handle.net/10589/226815