Reverse engineering of a railcar prototype via energetic macroscopic representation approach. (15th March 2016)

• Record Type: Journal Article
• Authors: Agbli, Kréhi Serge; Hissel, Daniel; Sorrentino, Marco; Chauvet, Frédéric; Pouget, Julien
• Is Part Of: Energy conversion and management. Volume 112(2016)
• Page Start: 61
• Page End: 80
• Publication Date: 2016-03-15
• Subjects: Energetic macroscopic representation -- Railcar -- Regenerable braking -- Powertrain -- Multiphysics modelling -- Hybridization analysis; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2015.12.072
• Languages: English
• ISSNs: 0196-8904

Abstract

Highlights: A complex EMR model of a new railcar range has been developed. A satisfactory assessment of the fuel consumption of the railcar. The significant potential benefits are attainable by hybridizing the original railcar. The regenerative braking can provide up to 240 kW h saving. Abstract: Energetic Macroscopic Representation (EMR) modelling approach is proposed to perform model-based reverse-engineering of a new railcar range, having six propulsion units, each consisting of a diesel engine and a traction motor. Particularly, EMR intrinsic features were exploited to perform phenomenological structuration of power flows, thus allowing proper and comprehensive modelling of complex systems, such as the under-study railcar. Based on some prospective real trips, selected in such a way as to enable realistic evaluation of effective railcar effort, EMR-based prediction of railcar energy consumption is performed. Furthermore, physical consistency of each powertrain component operation was carefully verified. The suitability of EMR approach was thus proven effective to perform reverse-engineering of known specifications and available experimental data, with the final aim of reconstructing a high fidelity computational tool that meets computational burden requirements for subsequent model-based tasks deployment. Finally, specific simulation analyses were performed to evaluate the potential benefits attainable through electric hybridization of the original powertrain.